KOTRA Silicon Valley Forum Presents Benefits and Risks of the Metaverse

Under the theme of "The Metaverse is Yours," the Korea Trade-Investment Promotion Agency (KOTRA) in Silicon Valley, a non-profit agency operated by the South Korean government that serves as one of the 127 overseas KOTRA branches worldwide, held its annual convention, K-Global @ Silicon Valley 2022, from Nov. 7th-8th in Santa Clara, Calif. The event started with an information and communications technology (ICT) forum focused on innovation which included discussions about the metaverse and its four key aspects of content, platforms, networks, and devices. After welcoming remarks from Korean dignitaries, the event featured the following keynote speakers:

• Shilpa Kolhatkar, who serves as Global Head of AI Nations Business Development at NVIDIA, talked about how the metaverse is the next evolution of the internet, the home to connected virtual worlds and digital twins, and a place for real work as well as play. She said NVIDIA's platforms provide enterprises the ability to develop physically accurate, artificial intelligence (AI)-enabled, virtual simulations that are synchronized with the real world. Ms. Kolhatkar also noted that digital twins are transforming industries and scientific discovery, as well as enabling developers, researchers, and enterprises who use them to design, simulate, and optimize products, equipment, and processes in real-time, before ever going to production.
• Heesuk "Ricky" Kang, Head of Business at Naver Z, discussed how his company's ZEPETO Studio platform features 68 million Studio items sales created by over 2.3 million creators to 300 million users worldwide. Mr. Kang said ZEPETO, which is the fastest growing avatar platform in Asia, is popular among Gen Zs who express themselves while meeting, collaborating, and creating with others.
• Jason Mayes, Head of Business, Lead Web ML & AL Developer Advocate at Google, focused his presentation on TensorFlow.js, a library for machine learning (ML) in JavaScript. He explained how TensorFlow makes it easy for beginners and experts to create machine learning models for desktop, mobile, web, and cloud. Mr. Mayes added that data can be the most important factor in the success of a user's ML endeavors and TensorFlow offers multiple data tools to help consolidate, clean and preprocess data at scale. I appreciate his assertion that TensorFlow empowers "machine learning for everyone."

The next segment of the ICT Forum focused on a panel discussion. Shawn Flynn, Principal of Global Capital Markets and host of "The Silicon Valley Podcast," moderated an insightful discussion featuring Pouneh Kaufman, Group Project Manager at Microsoft, Ray Wu, Managing Partner at Alumni Ventures, and Sean Jun, Product Manager at XL8. Key points from the moderated session included:

• The metaverse is an evolution, not a revolution. And it is one that businesses should not ignore.
• The metaverse may profoundly change how businesses and consumers interact with products, services and each other (i.e., enriching the customer experience and introducing virtual products).
• The metaverse will help support sustainability efforts by saving both time and resources used to travel to attend meetings, lectures, and social gatherings (I expect the use of the metaverse will help companies achieve their environment, social, and governance goals).
• The metaverse allows the ability to collect new data on customers.
• The metaverse will have profound benefits in various sectors including education, healthcare, and e-commerce.

Image Credit: KOTRA Silicon Valley

The panel, however, presented a number of risks associated with the metaverse which will require new strategies and methods to build trust. What is more, as with Web 2.0 (the current internet), users of Web 3.0 will need to contend with cyberbullying and harassment issues, as well as identity theft, unauthorized data collection by corporations, and cybersecurity threats from malicious actors.

Lastly, the event featured an expo featuring metaverse and AI-related small- and medium-sized enterprises from Korea that showcased their products, services, and technology. While you can view a listing containing all of the exhibiting companies here, below are a few that I found of particular interest: 

• Corevalue Ltd. is developing a service that can help everyone manage their health conveniently and easily. Accordingly, a smart camera and telehealth app were developed and the Dr. Clobo brand was launched in August 2020. Its healthcare camera can take detailed pictures of the mouth, ears and nose, and based on this, non-face-to-face medical consultation and health management.
• Grebt developed a bloodless-based diabetes measurement sensor and diabetes measurement device that eliminates the fear of blood sampling and the pain of blood collection. Its urine glucose meter measures the concentration of glucose in urine and reacts blood glucose in urine. It consists of a strip, a disposable consumable that generates an electrochemical signal.
• NdotLight is the developer of NdotCAD, a 3D/AR/VR content design tool which allows any users including non-professionals to express and share their imagination in 3D with ease. The company has lowered the hurdle for 3D content creation by making intricate 3D design process easy with increased usability while maximizing output quality by applying advanced technologies. With their 3D engine, they serve enterprise clients also by providing customizable solution to meet any B2B needs.

As we transition into the post-pandemic era, the K-Global @ Silicon Valley event provided a good opportunity to explore the future of the metaverse, AI, and other ICTs. What benefits and risks do you think the metaverse will bring to consumers and businesses alike?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

Korean Companies Demonstrate Their Innovative Tech Solutions at TechCrunch Disrupt 2022

TechCrunch Disrupt resumed its in-person event in San Francisco from Oct. 18th-20th, 2022. The conference's purpose is to bring together the global startup community to discover insights, collaborate, and celebrate achievements that have defined each founder's journey and for those yet to come in the future. At the invitation of the Korea Trade-Investment Promotion Agency (KOTRA), a state-funded trade and investment promotion agency operated by the South Korean government, I had the opportunity to visit the conference's Korea Pavilion and meet with startup founders and their colleagues. Among the 20 great companies that demonstrated their innovative products and services at the pavilion, which was co-hosted by the Korea International Trade Research Institute (KITRI), there are a few are worth mentioning based on my professional and personal interests (the program book containing a description of all 20 companies may be viewed here).

Cochl created an artificial intelligence (AI) platform specializing in ambient sound recognition. Use cases include public safety (faster response to shooting incidents, vandalism detection for buildings, and violence prevention by scream/yell monitoring), traffic monitoring (automatic car accident report and illegal car honking noise monitoring), and autonomous driving (ambulance and police car siren detection for giving right-of-way action and car window break monitoring). Another valuable use case is in the defense sector by using smart glasses with gunshot analysis, submarine and torpedo type analysis, and surrounding environment monitoring with unmanned ground vehicles.

Dabeeo provides global geospatial information based on AI/ML (machine learning) technology by reading and interpreting the earth to help customers build or modify digital maps. Its STUDIO for maps is a SaaS platform that makes creating, editing, and managing map data convenient and intuitive to use. This website provides several examples of how retailers, showrooms, factories, stadiums, and exhibition centers are using the cloud-based platform.

TheWaveTalk developed a technology that uses laser multi-scattering and deep learning to measure foreign substances in water with great precision. Through the technology, they developed a home water quality meter called the WaTalk, which scatters light inside the water using a laser and analyzes small signals of fine particles such as bacteria, virus, organic pollutants, and microplastics to determine the degree of contamination. The company says its product is 20-50 times cheaper than professional measuring equipment.

Image: Willog

Willog is simplifying the complex cold chain industry. (A cold chain is a low temperature-controlled supply chain network.) The company's patent-based monitoring device collects various data during the entire logistics process, and displays it on a QR code. Willog's data monitoring device, the One Time QR (OTQ), which can be placed on vehicles, shipping containers or pallets, allows instant confirmation of temperature records by scanning the QR code with a smartphone camera and does not require other training or equipment. Effective field operation response is possible without extra time or procedures spent between the driver and the personnel to check the temperature. Where the device cannot be physically retrieved, Willog's OTQ-N uses near-field communication (NFC) to facilitate logistics monitoring within a flexible environment.

While KOTRA provides a useful service in the promotion of trade and investment with 128 Korea Business Centers located in 84 countries, the agency also facilitates global people-to-people exchange and technological exchange. I appreciate having the opportunity to meet with ambitious startup leaders who are building companies that improve the way we live, work, and play.

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

Report Explores How Mobile and Digital Technology Can Support Industry Decarbonization

According to a report conducted GSMA Intelligence, the research arm of the GSMA, a UK-based organization that represents the interests of mobile operators worldwide, "The use of mobile and digital technology is a key enabler of the decarbonization transition. Telecoms operators, vendors and supporting ecosystem partners play a key role in the move to digital and low-carbon economies, particularly where it involves the enterprise segment and asset-intensive sectors using technology to lower emissions." Supported Nokia, a Finnish multinational telecommunications, information technology, and consumer electronics company, Industry pathways to net zero: mobile and digital technology in support of industry decarbonization outlines "a high-level quantification of decarbonization and associated strategies for four key industries that account for 80% of global emissions – manufacturing, power and energy, transport, and buildings." The report also outlines "a set of forward-looking implications."

Addressing how smarter use of mobile and digital technology results in carbon savings, the report explains that the "implementation of specific mobile and digital technologies could result in substantial CO2 savings for each industry. In aggregate, the savings enabled by the technologies amount to just under 40% (equivalent to 11 gigatons) of the carbon emissions savings that these industries will need to achieve over the next decade, assuming an end goal of net zero by 2050." I appreciate how GSMA Intelligence puts this in perspective at an industry level:

• The annual global CO2 savings from smart manufacturing would equate to 28 million roundtrip flights from London to Los Angeles.
• The potential CO2 savings from using smart meters in North American residential premises would be enough to power 25 million homes (20% of households in the US) for a year.
• The savings from the switch to electric vehicles (EVs) worldwide would equate to removing 180 million petrol-fueled cars from roads over the next 10 years.

With respect to the specific technologies of IoT, LTE and 5G, the report imparts that "Digitization and decarbonization are enabled by a range of mobile connectivity products and network services working in sync with artificial intelligence (AI) and machine-learning algorithms in the cloud to drive productivity gains." GSMA Intelligence highlights ways "IoT sensors, LTE and 5G connectivity (including for private networks) are being deployed across the industries profiled in this analysis, along with a raft of other solutions."

• In manufacturing, smart factories are underpinned by IoT sensors, robotics and AI that automate dynamic shifts to production capacity and the remote repair of machine faults. This reduces reliance on manual labor, increases productivity and lowers overall factory energy consumption and emissions compared to premises not fitted with these technologies.
• In buildings, intelligent architectural design and the use of sustainable materials in the construction process are augmented by smart electricity and gas systems that optimize the use of energy based on occupancy levels and prevailing external climatic conditions. In homes, smart electricity meters are linked to smart home controls through a central interface that can offer energy savings of up to 5% and, in some cases, the ability to sell excess energy from the consumer to the grid.
• In transport, the use of on-board cellular telematics can improve shipping fuel efficiency and enable a more optimized model for cargo arrivals and departures from ports, due to reductions in idling time and better coordination with trucks for onward distribution of goods.

Having followed the rise of IoT and 5G mobile technology over the past few years, I concur that the "ubiquity of mobile and digital technologies in these examples demonstrates their ability to deliver greater energy efficiency and productivity for industries globally. This requires a long-term and holistic investment approach."

On the benefits of digitization going beyond decarbonization, GSMA Intelligence points out that "While industry decarbonization can help mitigate the risks of global warming, there are other important socioeconomic benefits." Examples include the following:

• Public health outcomes – Reducing CO2 in the power sector will result in lower concentrations of harmful particulate matter and gases such as nitrogen dioxide. A similar effect is expected to prevail as electric vehicles replace petrol- and diesel-fueled cars, and through a higher share of the population working at home.
• Economic diversification – Moving to digital operating models in industries such as manufacturing and transport will create new jobs and sources of national value growth. Digital operating models can also increase access to public services and civic engagement.
• Productivity – Digitization drives fundamental improvements in productivity, which form the basis of new business models across industries.

Lastly, GSMA Intelligence asserts that its "research demonstrates the clear, practical and beneficial impact of using mobile and digital technologies in the largest and most relied upon industries. These are, in the main, ready-made options." The research organization importantly adds that "While investment outlays and deployment costs are required (a particular challenge for smaller companies), these will decrease over time as scale grows. The long-term return on investment from a financial perspective (higher productivity) and sustainability angle (lower emissions) is highly significant. Market participants in the telecoms, media and technology sectors are unique in being both suppliers and consumers of the technologies. In this capacity, we hope this report and ensuing industry case studies add to the best practice driving decarbonization in the years ahead."

How do you think mobile and digital technology can support industry's path to decarbonization?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

WHO's First Global Report on AI in Health and Six Guiding Principles for Its Design and Use

According to a report published by the World Health Organization (WHO), "Digital technologies and artificial intelligence (AI), particularly machine learning, are transforming medicine, medical research and public health. Technologies based on AI are now used in health services in countries of the Organization for Economic Co-operation and Development (OECD), and its utility is being assessed in low- and middle-income countries (LMIC)."

The report, Ethics & Governance of Artificial Intelligence for Health, which is the result of two years of consultations held by a panel of international experts appointed by WHO, further says: Whether AI can advance the interests of patients and communities depends on a collective effort to design and implement ethically defensible laws and policies and ethically designed AI technologies. There are also potential serious negative consequences if ethical principles and human rights obligations are not prioritized by those who fund, design, regulate or use AI technologies for health. AI's opportunities and challenges are thus inextricably linked."

To limit the risks and maximize the opportunities intrinsic to the use of AI for health, the WHO provides the following six principles as the basis for AI regulation and governance:

Protecting human autonomy: In the context of health care, this means that humans should remain in control of health-care systems and medical decisions; privacy and confidentiality should be protected, and patients must give valid informed consent through appropriate legal frameworks for data protection.

Promoting human well-being and safety and the public interest. The designers of AI technologies should satisfy regulatory requirements for safety, accuracy and efficacy for well-defined use cases or indications. Measures of quality control in practice and quality improvement in the use of AI must be available.

Ensuring transparency, explainability and intelligibility. Transparency requires that sufficient information be published or documented before the design or deployment of an AI technology. Such information must be easily accessible and facilitate meaningful public consultation and debate on how the technology is designed and how it should or should not be used.

Fostering responsibility and accountability. Although AI technologies perform specific tasks, it is the responsibility of stakeholders to ensure that they are used under appropriate conditions and by appropriately trained people. Effective mechanisms should be available for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms.

Ensuring inclusiveness and equity. Inclusiveness requires that AI for health be designed to encourage the widest possible equitable use and access, irrespective of age, sex, gender, income, race, ethnicity, sexual orientation, ability or other characteristics protected under human rights codes.

Promoting AI that is responsive and sustainable. Designers, developers and users should continuously and transparently assess AI applications during actual use to determine whether AI responds adequately and appropriately to expectations and requirements. AI systems should also be designed to minimize their environmental consequences and increase energy efficiency. Governments and companies should address anticipated disruptions in the workplace, including training for health-care workers to adapt to the use of AI systems, and potential job losses due to use of automated systems.

As the WHO notes: "AI for health has been affected by the COVID-19 pandemic. Although the pandemic is not a focus of this report, it has illustrated the opportunities and challenges associated with AI for health. Numerous new applications have emerged for responding to the pandemic, while other applications have been found to be ineffective. Several applications have raised ethical concerns in relation to surveillance, infringement on the rights of privacy and autonomy, health and social inequity and the conditions necessary for trust and legitimate uses of data-intensive applications."

"While the primary readership of this guidance document is ministries of health, it is also intended for other government agencies, ministries that will regulate AI, those who use AI technologies for health and entities that design and finance AI technologies for health."

The report importantly adds:

Implementation of this guidance will require collective action. Companies and governments should introduce AI technologies only to improve the human condition and not for objectives such as unwarranted surveillance or to increase the sale of unrelated commercial goods and services. Providers should demand appropriate technologies and use them to maximize both the promise of AI and clinicians' expertise. Patients, community organizations and civil society should be able to hold governments and companies to account, to participate in the design of technologies and rules, to develop new standards and approaches and to demand and seek transparency to meet their own needs as well as those of their communities and health systems.

Do you agree with the six principles as the basis for AI regulation and governance? What are you recommendations for how AI can be used for health?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

AI Can Have a Transformative Impact in Low- and Middle-Income Countries, Says GSMA Report

"Around the world, artificial intelligence (AI) is automating functions and making new services possible with breakthroughs in cheap computing power, cloud computing services, growth in big data and advancements in machine learning (ML) and related processes," according to a study that aims to understand the current and potential use of AI by startups and small and medium enterprises (SMEs) in low- and middle-income countries (LMICs) in four regions: Sub-Saharan Africa, North Africa and South and Southeast Asia.

The report, which was produced by the GSM Association (GSMA), a UK-based organization representing the interests of mobile operators worldwide, asserts that "AI can radically alter and improve the way governments, organizations and individuals provide services, access information and improve their planning and operations."

Mapping "a sample of 450 start-ups by sector in alignment with the UN Sustainable Development Goals (SDGs) and, based on interviews with AI experts in LMICs," the report explores "trends and challenges in business models, barriers to innovation and the ethical and responsible use of AI." In doing so, the study answers the following research questions:

• What is the status of AI use in LMICs?
• Which sectors, geographies and business models are showing the most promise, and why?
• What are some of the barriers to implementing AI solutions in LMICs?
• How can AI be used ethically to accelerate the achievement of the SDGs?

Top AI use cases in LMIC include agriculture, administration and business processes, cities and infrastructure, climate change, disaster management, education, finance and microlending, government and public services, healthcare, and identity. In explaining the use cases by sector verticals, the report says: "Business intelligence and analytics had the highest number of use cases as it captures a wide range of business-to-business (B2B) solutions, from enhanced retail market analysis and predictive decision making to customer service. Customer service chatbots, automated IT consulting, big data analytics and automated records are some examples of AI use cases."

As for healthcare, this rapidly growing sector "had the second highest number of use cases and clearly benefits from AI solutions, including sophisticated diagnosis and treatment options, hospital management systems, lifestyle change recommendations and healthy eating habits." The report further notes that "[f]ood and agriculture, financial services, education and retail and consumer goods followed these sectors. Food and agriculture employs a range of AI-based services, including services for identifying and remedying crop diseases, linking producers more effectively to buyers and markets and helping farmers maximize crop yields based on climatic and soil conditions."

As for use cases by country and region, the report identified a few AI innovation hotspots (see map above). "India," for example, "was the most represented country in our sample. The country accounted for over 40 percent of the sample (180 use cases), indicating a high level of innovation and AI uptake in the country. Far more cases were identified in India, but were excluded due to limited alignment with development outcomes, apart from general economic development. Nigeria and South Africa were the next two most represented nations in the sample with 42 and 38 use cases, respectively. China was excluded from the study, along with the rest of East Asia, which are emerging as centers of AI innovation and investment. For example, in 2017, China submitted approximately 1,300 AI and deep learning-related patents, compared to 220 by the United States."

Data, ICT infrastructure and hardware challenges create barriers to implementing AI in LMICs. Such challenges include the availability, accessibility and quality of data, access to reliable and affordable internet, lack of access to sufficient computing power, increasing digital inclusion and connectivity including device access, ownership and capability, and unreliable power infrastructure.

Human capital and lack of funding and automation present additional barriers. According to the GSMA, "While there is growing access to upskilling and training in AI, many countries still lack a steady pipeline of home-grown talent and skilled AI development talent. [...] The lack of mentorship available to start-ups developing AI-based solutions is also a constraint in many countries."

Regarding the lack of investment, the report explains that "AI-based solutions typically need a lot of investment. Unlike countries such as China and the United States, investment and funding are extremely limited in most LMICs. Countries in Africa and South and Southeast Asia that appear to have higher levels of investment include India, Kenya, Malaysia, Thailand and South Africa."

On the topic of the ethical use of AI in LMICs, the report points out that "To genuinely contribute to the SDGs, AI innovators need to eliminate the potential negative impacts of their AI processes. AI applications should be ethical by design to prevent and mitigate any potential negative impacts on users, workers, communities and the environment."

Moreover, "The application of existing laws, regulations and privacy principles, such as the GSMA Mobile Privacy Principles, can help mitigate privacy and ethics risks associated with AI. In addition to these frameworks, the GSMA recommends the adoption of the following principles by all stakeholders using AI for social good."

• "Do no harm: Development and deployment of AI systems should respect human rights and should not cause human rights harm to individuals or groups. Particular care should be given to preventing harm to vulnerable individuals or groups."
• "Be inclusive: AI stakeholders should support inclusion and equity, and should strive to ensure that the benefits of their AI-based technologies are broadly accessible.
• "Be fair: AI systems should incorporate human oversight. All stakeholders should strive to ensure that the data used in AI is accurate and not unfairly biased. AI should not be used to make decisions that may affect any group or individual in an unfair or discriminatory way (e.g. discrimination based on protected characteristics such as race, gender, etc.).
• "Ensure transparency: Individuals should be informed when they are communicating with AI-powered systems instead of a human (e.g. conversational AI). Decisions made with AI should be clearly explained to the individuals affected.
• "Embed accountability: All AI stakeholders should be accountable for their use of AI and should promote these principles with the third parties they engage for social good purposes.
• "Adopt privacy and ethics by design: AI systems should be designed and deployed according to privacy and ethics by design ethos or methodology at each stage of the life cycle, with input from relevant teams.
• "Advance security and safety: Access to AI systems and their underlying data should be controlled and subject to audits or other accountability measures. State-of-the-art security measures should be used wherever possible. All AI experts and practitioners should implement best practices in security.
• "Support sustainability and societal well-being: Sustainability and societal well-being should be considered in the development and deployment of AI systems."

Maintaining business interests in many of the countries covered in this report, I concur with the GSMA that AI can have a transformative impact on LMICs. Such transformation, however, will require investments from the private sector and governments to overcome the aforementioned barriers to implementing AI. What is more, media sources are starting to present reports about the misuse of the technology. It is imperative that all stakeholders using AI adopt the GSMA's recommendations for using AI for social good.

Do you agree with the report's findings? How are you engaging in the development of AI solutions in LMICs?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

Innovative Startups Pitch at Silicon Valley Funding Summit 2020

Once again, I attended the annual consumer and electronics show in Las Vegas, Nev. Owned and produced by the Consumer Technology Association (CTA)®, a Virginia-based trade organization. CES® is promoted as "the world's largest and most influential tech event." While a separate post will focus on my experience of attending CES 2020, this post addresses an event, "Silicon Valley Funding Summit 2020," I attended on Jan. 6th.

Co-produced by Angel Launch, which connects Silicon Valley, American and foreign financial professionals and investors to global startups and private companies for high-level networking and deal-making to build successful ventures, and ENRICH in the USA, which establishes a network of European research and innovation centers and hubs throughout the United States acting as a central contact point for European research and innovation actors, the Silicon Valley Funding Summit aims to connect accredited investors and corporate partners to global startups. Those startups presenting to a panel of investors and audience come from a variety of sectors including consumer and enterprise apps; devices and platforms; hardware; software; data analytics; robotics; machine learning; smart devices; digital health; fintech; and cybersecurity.

Some of the companies that I found of particular interest include:

• BARU's mission is to empower the customer you to create a home that fits your unique lifestyle and personality. Our made-to-measure furniture can fit right in. Design every dimension to the inch and preview it in your space with our Augmented Reality app.
• Brilliant Sole focuses on merging footwear and virtual reality.
• Calamus Electric Private Limited (Calamus) promotes itself has built the world's first e-bike with an inbuilt TFT touchscreen that interacts with the Ultrabike's advanced features.
• Sensors provided by Caregiver Smart Solutions track movement and patterns to provide caregivers with some reassurance that things are as they should be, without the use of invasive video cameras or wearable tracking devices.
• CloudBackend provides a world-wide service for accelerating applications and harvesting data through a distributed cloud with intelligent data management. The platform is designed for smart vehicles, telecom infrastructure, public clouds, on-premise, smart devices in homes and offices, and in between.
• Cyber Reconnaissance, Inc. (CYR3CON) specializes in combining artificial intelligence with information mined from malicious hacker communities to avoid cyberattacks.
• Dr. i-Coach® by Eyes4lives is a patented sensor and software package that sits on top of a laptop/monitor and monitors the users blink rate, sitting height, screen distance, screen time and ambient lighting. The product will alert the user if they are in violation of any of the above-mentioned factors and will coach them on developing and maintaining proper sitting and screen use habits.
• FATRI (Xiamen) Technology Co., Ltd. (FATRI) focuses on the development of new materials, chip design (MEMS Chip & AI Chip), sensors, data acquisition designed assemblies and AI data analysis platforms.
• Joué makes MIDI instruments for creative musicians. The Joué Board is a MIDI controller to play drums, guitar, keyboard and more.
• MJN Neuroserveis developed MJN-SERAS, an earpiece that records brain activity from the ear canal. In combination with AI algorithms the device triggers a warning signal minutes before an epileptic seizure occurs and also records it during the onset.
• UltraUVTech revolutionizes the way consumers disinfect wet and dry surfaces through its reliable ultraviolet sterilizing technology.

The summit presented me with the opportunity of sitting on a panel of accredited investors. The panelists were asked to briefly provide advice to the presenting entrepreneurs and audience members. I recommended that entrepreneurs adopt the mantra "if you do not know your numbers, you do not know your business." Entrepreneurs should know various financial metrics for their startup such as gross gross profit margins; expenses as a percentage of their gross profit; annual operating expenses segmented by sales and marketing, general and administrative (G&A), and research and development (R&D); and cost of revenue (sales).

In addition, entrepreneurs should comprehend eight risk factors that may prevent their startup from becoming a successful (i.e., profitable) venture.

While I found that several companies are developing useful products and services, I was underwhelmed by many of the actual presentations. First, most entrepreneurs did not complete their presentations within the time allowed. Being prepared including practicing the pitch will go a long way in presenting a polished presentation.

I also found many entrepreneurs spent too much time explaining the problem they are trying to solve, but not enough time to thoroughly explain the solution their business is providing to their customer.

And when pitching to prospective investors, a strong presentation should include the "WOW!! Factor" -- why are customers excited to do business with you?

Mike Grigg, who provides soft skills leadership coaching in storytelling, produced the images below on how to improve your presentation skills, which my colleagues and I find useful.

I am grateful for having the opportunity to attend the Silicon Valley Funding Summit 2020. The organizers did a great job in producing an event both entrepreneurs and investors found valuable.

What advice do you have for startup entrepreneurs?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

More Than Four in Five Mobile Connections in Asia Will Be Smartphones by 2025, Says GSMA Report

Having worked in the region over the past several years, I can attest to a report's assertion that "[m]obile internet uptake is spreading rapidly across Asia Pacific, and smartphone ubiquity has resulted in consumers continuing to transition from connectivity to digital services." Authored by GSMA Intelligence, the research arm of the GSMA, The Mobile Economy Asia Pacific 2019 further says the size and diversity of the region, however, "mean countries are at different stages of digital development. Consequently, the policy frameworks for a digital society vary across the region as national governments address their own unique challenges."

The report adds: "For some Asian markets, 2019 will see 5G become a reality as mobile operators move from development and testing to commercial deployment. For many countries in the region, however, 5G deployment is several years away so 4G will remain pivotal to the development of a digital society. Meanwhile, other critical components, such as payments and identity, are evolving rapidly, and governments will need to ensure they continue to develop policies that are modernized and relevant."

The report reveals that:

• Mobile operators are forecast to invest $574 billion (capex) on new networks between 2018 and 2025, almost two-thirds of which ($370 billion) will be spent on new 5G networks. China alone is forecast to invest $184 billion on 5G by 2025;
• 4G became the most dominant mobile technology in Asia in 2018 (52 percent of connections), forecast to rise to 4.8 billion by 2025, and will grow to account for more than two-thirds of regional connections by 2025. Around 18 percent of connections will be running on 5G networks by this point;
• More than four in five mobile connections in Asia will be smartphones by 2025, up from 61 percent in 2018;
• There were 2.8 billion unique mobile subscribers in Asia at the end of 2018, equivalent to 67 percent of the region's population. The number of subscribers is forecast to increase to 3.1 billion by 2025 (72 percent of the population), though the growth rate is slowing as many key markets approach saturation;
• Almost all new subscribers to be added in the region between 2018 to 2025 will come from six countries: India, China, Pakistan, Indonesia, Bangladesh and the Philippines;
• In 2018, mobile technologies and services in Asia Pacific generated $1.6 trillion of economic value, equivalent to 5.3% of regional GDP. This contribution is forecast to surpass $1.9 trillion by 2023; and
• Asia Pacific's mobile ecosystem directly and indirectly employs more than 18 million people, and last year contributed $165 billion in public sector funding via general taxation (excluding regulatory and spectrum fees).

Infographic: GSMA Intelligence

As the use of smartphones become more ubiquitous in Asia Pacific coupled with the gradual deployment of 5G networks in the near future, we will see a rise of business opportunities across a multitude of sectors including artificial intelligence and machine learning, cloud computing, connected devices (IoT), digital health, e-commerce, and fintech, just to name a few.

What services or products do you see will make the greatest impact in the region's mobile economy?

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.

Will Your Company Appoint an AI Director to Its Corporate Board?

Photo illustration by Slate

Leadership and artificial intelligence (AI) are two distinctive topics that are discussed on this blog. An article, "Why Not Appoint an Algorithm to Your Corporate Board?" authored by Will Pugh and published by Slate merges the two topics together. Mr. Pugh says board of directors, charged with overseeing chief executives and their management teams, face two key difficulties: "first, that boards typically consist of notable people with limited time and attention spans, and second, that their flow of information regarding corporate affairs is typically controlled by the CEO." Referencing a BBC article, Mr. Pugh writes how Deep Knowledge Ventures, a Hong Kong-based venture capital firm focusing on drugs for age-related diseases, "has raised a tech-forward way around these conundrums: appointing an algorithm to one of the directors' chairs."

According to the BBC, Vital, a program by UK-based Aging Analytics, "will vote on whether to invest in a specific company or not. ... [Deep Knowledge Ventures] said that Vital would make its recommendations by sifting through large amounts of data." Furthermore, "The algorithm looks at a range of data when making decisions - including financial information, clinical trials for particular drugs, intellectual property owned by the firm and previous funding."

Mr. Pugh notes that "as of now, AI directors would be illegal under U.S. corporate law, which requires directors to be 'natural persons.' But the idea of putting AI on a corporate board isn't as far-fetched as it may seem. In a 2015 study by the World Economic Forum, which surveyed over 800 IT executives, 45 percent of respondents expected that we'd see the first AI on a corporate board by 2025, and that such a breakthrough would be a tipping point for more."

With respect to the two aforementioned difficulties boards encounter, (1) limited time and attention spans and (2) their flow of information regarding corporate affairs is typically controlled by the CEO, Mr. Pugh suggests thinking "of how much further it could go if a company were to supplement" high-level "supervision from, say, sophisticated AI that could independently monitor fine-tuned goals ... and even balance competing interests on a more nuanced level. It's the kind of technology that could help those human board members transition from high-level supervisory entities to effective micromanagers."

What is more, "Consider the data-hungry environments where AI thrives. Machine learning is ideal when you need to find hidden patterns in vast troves of data. An AI director could consume huge amounts of information about the company and the business environment to make good decisions on issues like the future demand for the company's products or whether the company should expand to China. This is exactly how the first AI director, appointed by the Hong Kong company Deep Knowledge Ventures, is being used: It's tasked with consuming data about life science companies and then voting on which companies are good investments. The company says that it relies on the AI's recommendations by refraining from making any investments that the AI doesn't approve—which they say has helped with eliminating some kinds of bias and avoiding 'overhyped' investments."

Mr. Pugh asks: "But why go to the extreme of giving A.I. its own seat when, theoretically, the board could just consult such algorithmic assessments to inform its decisions? This gets back to the issues of time, loyalty, and access to information. Unlike a human, an AI director is appealing as a potential independent tiebreaker on any disagreement between the human board members. What's more, if such algorithms cast votes, it will be harder for other directors to disregard those votes, and it will force those directors to find compelling reasons to oppose them. In some cases, an AI director's vote could be a red flag, an antidote to groupthink. In others, it may force human directors to confront potential biases in their thinking, like loyalty to a particularly charismatic CEO. Think of what an AI director at General Electric might have focused on in recent years when the company appeared to disregard its plummeting cash flow and mounting pension liabilities from operations over many years."

Crucially, Mr. Pugh observes "[t]here are, of course, limitations and issues to overcome before giving software a seat at the directors’ table. For one, many forms of AI 'learn' from human-generated and human-curated data—which has been known to replicate human bias. This kind of bias can be hard to fix because it can creep in at many different stages of AI training, including the goals programmers assign the AI to achieve, the data sets they feed it, the data attributes they choose to focus on, and the data they use to test it. Many programmers are becoming more cognizant of these issues, however, and are looking at better ways to address these biases in the process of developing these tools—including projects like AI that aims to 'de-bias' other AI tools."

Moreover, "Deep learning techniques are currently 'black boxes.' A self-driving car may be able to identify a crosswalk, and a valuation algorithm may be able to say that a company is worth $X, but if AI directors are going to interact with shareholders and human directors, they need to be able to explain their conclusions. If we can't look under the hood and see their reasoning, AI directors will be hard to trust, and courts won't be able to ensure that they are fulfilling their legal duties to provide shareholders 'candor'—i.e., all information that would be important to a shareholder. Under securities law, one of the most common disclosure items for directors is an explanation of how and why directors are handling risk in a specific way. If machine learning algorithms can reveal their internal logic and are designed to analyze and communicate such risks well, they may even do a better job at providing such disclosures by helping humans focus on the right details by filtering out noise in data.

"This also gets at another advantage that a transparent algorithm could have: a refreshing lack of personal ambition or interests. Assuming sufficient advancement in AI technology, shareholders and stakeholders alike could trust AI directors to be forthcoming about why they are taking a specific action—an attribute not always found in their human counterparts. Courts have recognized that, while directors may ostensibly be trying to benefit shareholders, there's an 'omnipresent specter' that members of the board are, intentionally or not, actually pursuing self-interest. On a hybrid board with both humans and AI, the AI could provide shareholders, as well as other directors, with a more objective analysis when it comes to, say, questions like how a potential merger could affect directors own net worth."

Mr. Pugh writes that "legislative proposals in the U.S. call for directors to consider shareholders and other stakeholders' interests. This could be achieved by requiring a subset of human directors to look out for employees while others remain focused on shareholders—or it could be achieved by fine-tuning an individual AI director's ultimate goals. If AI technology advances to the point where AI directors could explain how they reach their conclusions, then a single AI director could, for example, be programmed to consider both shareholder and stakeholder interests in a more transparent way than a human director could."

In my experience of serving on the board of directors of several companies, I can attest to the problem of limited time, loyalty and access to information. While AI is not a complete solution to solving corporate governance issues or strategic planning, I see value in including an AI director. Doing so could provide objectivity that will force human directors to confront there biases or determine the impact of a decision through machine learning that human directors could not ascertain on their own.

What do you think? Will your company appoint an AI director to its corporate board if or when it is lawfully to do so?

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.

GSMA Report Says Mobile Technology Will Enable Access to Life-Enhancing Services in the Pacific Islands

A post that I published in this forum in 2008 focuses on a project my colleagues and I developed in utilizing information and communications technology (ICT) to implement social and economic development initiatives in the Federated States of Micronesia (FSM). One significant outcome of our proposal was to create a digital strategy to be incorporated into the FSM's national development strategy. Eleven years later, I read with great interest a report, The Mobile Economy Pacific Islands 2019, that says "[m]obile technology can play a pivotal role in the digital transformation of the Pacific Islands, enabling access to life-enhancing services in areas such as health and education, while proving a catalyst for innovation and economic growth, with the promise of new jobs and increased tax revenues."

Authored by GSMA Intelligence, the research arm of the UK-based GSMA, below are the report's findings:

• Mobile helping to boost financial inclusion: The Pacific Financial Inclusion Programme (PFIP) was launched in 2008 and has funded 44 projects with financial service providers helping more than 2 million Pacific Islanders access formal financial services;
• The ongoing shift to mobile broadband and digital transformation: at the end of 2018 mobile internet penetration in the region was the lowest of any region in the world at 18 per cent. However, 4G connections in the Pacific Islands are set to account for more than half of total connections by 2023, doubling the figure from the end of 2018 and increasing access to services;
• Infrastructure challenges: Many countries in the Pacific Islands region face issues around insufficient infrastructure. Several countries are yet to complete the digital switchover process, including Papua New Guinea, Tonga and Solomon Islands; and
• Unlocking the full potential of mobile: The upcoming World Radiocommunication Conference will be one of the best opportunities for governments and industry to identify a significant amount of harmonized millimeter wave spectrum, which will result in massive economies of scale for 5G in the future.

Infographic: GSMA
Intelligence

The report encouragingly explains: "Mobile phones are bringing internet access to previously unconnected populations across the world, particularly in developing regions such as the Pacific Islands where there is a lack of alternative access technologies."

However, "Countries across the Pacific Islands still face significant challenges around funding infrastructure to provide mobile and internet access to their populations, which in turn reduces the ability of governments and policy-makers to address social and economic challenges. Providing mobile coverage is a particular challenge in a region often described as 'sea locked,' with large segments of the population living in remote and often inaccessible areas."

Further on the topic of the challenges of mobile connectivity in the Pacific Islands, the report notes:

The GSMA Mobile Connectivity Index measures digital inclusion in 163 countries across the world, including six countries in the Pacific Islands. The index is built around four key enablers of mobile internet connectivity, critical to creating the right conditions of supply and demand for mobile internet connectivity to flourish:

• infrastructure: the availability of high-performance mobile internet network coverage
• affordability: the availability of mobile services and devices at price points that reflect the level of income across a national population
• consumer readiness: citizens with the awareness and skills needed to value and use the internet and a cultural environment that promotes gender equality
• content: the availability of online content and services that are accessible and relevant to the local population.

There are many aspects of our 2008 proposal remain relevant in 2019 of using mobile technology as a pivotal role in the digital transformation of the FSM and throughout the Pacific Islands. Specifically, with the expansion of mobile technology, Pacific Islanders will be able to access digital health (mHealth), education, and financial technology (fintech) services. This presents a great opportunity for technology developers and investors to collaborate and support local small businesses.

In addition, with an early roll out of 5G services in 2020 and a projected 19,000 5G connections in 2025 (see left chart), frontier technologies such as artificial intelligence, blockchain, IoT and advanced data analytics will become available. "The Pacific Islands region might not be one of the first to roll out 5G services but it can benefit from a mature ecosystem and global economies of scale to see 5G develop in the same way as LTE has done in the region. New submarine cables with improved capacity and other technical advancements are setting the stage for advanced broadband services, including 5G."

What online content and services are you developing that are accessible and relevant to Pacific Islanders?

Aaron Rose is a board member, corporate advisor, and co-founder of great companies. He also serves as the editor of GT Perspectives, an online forum focused on turning perspective into opportunity.

EIU Report Explores Different Scenarios Around the Economic Impact of Machine Learning

"There is more uncertainty around advances in artificial intelligence (AI) and one of its major sub-sets, machine learning, than the current debate suggests, particularly with regard to the technology's impact on society and the economy," explains The Economist Intelligence Unit (EIU) in a report entitled Risks and rewards: Scenarios around the economic impact of machine learning. "No doubt the advances have indeed been incredible and advocates are right to highlight them. A decade ago few believed that a car could drive on its own, even in a controlled environment, or that an algorithm could learn how to label and organize photographs. Yet both of those are now possible and various forms of AI are performing new tasks it seems on a weekly basis."

Commissioned by Google, The EIU report is based on the results of econometric modeling of three scenarios covering five countries—the US, UK, Japan, South Korea and Australia—and Developing Asia as a region. In addition, the report presents qualitative scenarios for four industries: manufacturing, healthcare, energy, and transportation.

Impact on GDP and productivity

With respect to the three econometric scenarios, The EIU uses its current forecast to 2030 as a baseline. The scenarios are:

Scenario #1: Greater human productivity through upskilling

"Scenario #1 assumes a higher degree of complementarity between human skills and AI than does the baseline and that governments will invest more in upskilling than current trends suggest. In the results, every country or grouping covered benefits, but some more than others. Australia, where growth in services is becoming more important for incremental economic growth than commodity exports, would see the greatest gains. The gains elsewhere would be more modest by comparison; although in this scenario, the UK's productivity rises to slightly positive from our baseline forecast, which is for a slight decline."

Scenario #2: Greater investment in technology and access to open source data

"Scenario #2 assumes investment in access to open source data, tax credits to spur private sector adoption of machine learning, and advances in computing efficiency drive hardware costs down. This scenario yields the most encouraging results insofar as economic growth is concerned. Each of the five countries, as well as Developing Asia as a group, experience higher levels of growth relative to our baseline forecast. Australia, again, along with Developing Asia, reap the greatest rewards from promoting investment in this scenario, but all of the countries covered see GDP rise by at least 1% above the baseline between now and 2030."

Scenario #3: Insufficient policy support for structural changes in the economy
"Scenario #3, which is the one negative scenario among the three, assumes the substitution effect for labor dominates due to inaction in workforce development—or more simply, skills— and a lack of national data sharing schemes. The losses are substantial compared to the baseline. The UK and Australian economies actually shrink in US dollar terms versus today, as a result, with the UK's economy becoming US$420bn smaller in absolute terms and the Australian economy US$50bn. The US, Japan and Developing Asia still grow in this scenario, but their economies are all significantly below the baseline, with the US and Developing Asia both off by around US$3trn."

The industries

The qualitative scenarios look at four industries: manufacturing, healthcare, energy and transportation, which are provided below in its entirety from the report's Executive Summary.

Manufacturing

Employment in manufacturing has become a headline issue with the rise of populism in certain developed countries. When discussing AI, it's important to differentiate automation in hardware, such as robotics, from automation in software, AI and its sub-sets. The former has already had a significant effect on labor demand in the sector and while the latter may contribute to this trend, its impact has been less direct, at least to date.

When manufacturing firms talk about AI, they talk about creating greater efficiencies in their supply chains, reducing maintenance costs and moving towards batch production. Each of these may or may not result in the elimination of low wage jobs, but they will almost certainly create high wage ones, albeit not at a one-for-one ratio. The speed at which firms turn towards automation in both hardware and software depends on the 'payback period,' a measure which weighs the cost of investment in automation versus that of the cost of local labor."

Healthcare

As a knowledge industry, healthcare is ripe for AI and there are a variety of applications already in place. It's being used in the discovery process for new drugs, to save costs in both prevention and treatment, and to augment the abilities of practicing physicians and clinicians.

Yet there are constraints. The healthcare sector has traditionally been slower than most sectors to adopt innovations. That may be changing, however slowly, but there are other hurdles that need to be overcome. One is the issue of privacy. Patients are understandably sensitive about their personal data being shared and unless they can be assured their data will only be used for specific and agreed purposes, they may not agree to sharing it at all. That would hinder the use of AI considerably, dependent as it is on data for developing solutions.

Energy

AI is expected to have the most significant impact on the energy sector in transforming generation, transmission and distribution into a more coherent system. This means, among other things, creating pricing systems based on probabilistic models and developing smart grids that can better deal with the issue of intermittency, or the fact that the wind doesn't always blow and the sun doesn't always shine. Solving for intermittency will allow electricity providers to maximize their use of green energy.

This does not come without risks. Smart grids, while more efficient than current analogue grids, are exposed to new and greater risks from cyber-attacks, which, in turn, creates national security concerns. That has knock-on effects on the willingness of local governments to integrate their grids and share their data.

Transportation

While autonomous vehicles have captured much of the public's attention, even though they may still be far off, AI is already making major contributions to the speed and safety of public transport. In many cities, AI being used to balance the flow of passengers across different modes of transport and data received from sensors around cities, combined with AI, are helping to make traffic flow more smoothly.

The advent of autonomous vehicles nevertheless remains in the fore of people's minds in this area. Besides the obvious issue of its impact on employment, there are regulatory and privacy concerns, as well as the question of liability when, inevitability, a driverless vehicle becomes involved in an accident, fatal or otherwise.

The report also identifies five approaches to grounding the discussion in reality.

Managing expectations. "In the near-term, AI will be neither utopian nor dystopian. It will provide new benefits and it will create new problems. Exaggerating its upsides is as detrimental to the debate as is exaggerating its downsides."

Better communication. "There are many understanding gaps when it comes to AI, but one of the most important to bridge is that between developers and businesses and government institutions. The former are often only dimly aware of what the latter two really need, and the latter, in turn, are often only dimly aware of the potential solutions the former could provide. A more robust and frequent exchange of information, capabilities and needs would help to remedy this."

Acknowledging the risks. "It is important to acknowledge that AI presents risks to employment, as well as privacy, and to start finding solutions to these and other issues rather than encourage complacency or resignation through unshakeable confidence."

Improving trust and transparency. "'Trust us' or trust the algorithm is not a viable strategy for gaining widespread acceptance of AI and its various subfields. Developers and users alike need to make known what they are doing and how they are doing it, in a way that is both meaningful given the usage context and practical given technological constraints."

Educating the public. "Gaps in knowledge and understanding are filled more quickly than ever with misinformation and distortion. The public needs an explanation of what AI is and does, and as simply as possible."

Lastly, the report importantly notes: "Policymakers, for their part, face a number of choices as regards AI and its impact." These choices include investing in skills and training, dealing with data, and investing in R&D and technology.

How do you see artificial intelligence's impact on society and the economy?

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.

Artificial Intelligence is the Epicenter of Web 3.0

A friend recently noted that the current version of internet, which is often referred as Web 2.0, has matured. Such maturity has led to a stagnation in the production of innovative products and services by startups and large corporations alike. Following his observation, which I happen to agree with, he asked, "What is next for the internet?"

In an article published by the New York Times in 2006, John Markoff wrote, "From the billions of documents that form the World Wide Web and the links that weave them together, computer scientists and a growing collection of start-up companies are finding new ways to mine human intelligence."

The goal of the computer scientists, says Mr. Markoff, "is to add a layer of meaning on top of the existing Web that would make it less of a catalog and more of a guide — and even provide the foundation for systems that can reason in a human fashion. That level of artificial intelligence, with machines doing the thinking instead of simply following commands, has eluded researchers for more than half a century."

"Referred to as Web 3.0," notes Mr. Markoff, "the effort is in its infancy, and the very idea has given rise to skeptics who have called it an unobtainable vision. But the underlying technologies are rapidly gaining adherents, at big companies like I.B.M. and Google as well as small ones. Their projects often center on simple, practical uses, from producing vacation recommendations to predicting the next hit song."

11 years later, The Economist published an article about the race to dominate artificial intelligence (AI). "An exponential increase in the availability of digital data, the force of computing power and the brilliance of algorithms has fueled excitement about this formerly obscure corner of computer science," the article explains. "The West's largest tech firms, including Alphabet (Google's parent), Amazon, Apple, Facebook, IBM and Microsoft are investing huge sums to develop their AI capabilities, as are their counterparts in China. Although it is difficult to separate tech firms' investments in AI from other kinds, so far in 2017 companies globally have completed around $21.3bn in mergers and acquisitions related to AI, according to PitchBook, a data provider, or around 26 times more than in 2015."

I agree with the assertion that "over the next several years, large tech firms are going to go head-to-head in three ways. They will continue to compete for talent to help train their corporate 'brains'; they will try to apply machine learning to their existing businesses more effectively than rivals; and they will try to create new profit centers with the help of AI."

The Dec. 7, 2017 article continues to explain how AI will be used in machine learning, autonomous driving, augmented reality (AR).

In addition, the article importantly notes:

Artificial intelligence is also being applied in the corporate world. David Kenny, the boss of Watson, IBM’s AI platform, predicts that there will be "two AIs": companies that profit from offering AI-infused services to consumers and others which offer them to businesses. In practice, the two worlds meet because of the tech giants' cloud-computing arms. Providers are competing to use AI as a way to differentiate their offerings and lock in customers. The three largest—Amazon Web Services, Microsoft’s Azure and Google Cloud—offer application-programming interfaces (APIs) that provide machine-learning capabilities to other companies. Microsoft's cloud offering, Azure, for example, helped Uber build a verification tool that asks drivers to take a selfie to confirm their identities when they work. Google Cloud offers a "jobs API," which helps companies match jobseekers with the best positions.

As for augmented reality, "Mobile apps like Snap, a messaging app, and the game Pokémon Go are early examples of AR. But AR could more radically transform people's relationship with the internet, so that they consume digital information not from a small screen but via an ambient, ever-present experience. AR devices will offer portable AI capabilities, such as simultaneous translation and facial recognition."

We have embarked upon the Web 3.0. What are your predictions for the application of artificial intelligence?

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.

ROI3 and Entreprov to Join ITU's Focus Group on Machine Learning for Future Networks Including 5G

Image: http://ow.ly/4e7730gLyby

In a post on this blog dated Feb. 27, 2016, I write how 5G is a new wave of mobile technology that will bring drastic change. The flow of high volume of data with low latency will bring changes industrialized and developing countries alike will see in various sectors including connected devices (IoT), autonomous vehicles, virtual reality, artificial intelligence and machine learning. While the business model for some of these emerging technologies are still being crafted and tested, the research and development is happening now and I am regularly exploring opportunities to learn more about these technologies. Therefore, I am proud to announce that ROI3 has joined the International Telecommunication Union's Focus Group on Machine Learning for Future Networks including 5G.

In a press release, the Geneva, Switzerland-based ITU says the purpose of the focus group, which goes by FG-ML5G, is to "establish a basis for ITU standardization to assist machine learning in bringing more automation and intelligence to ICT network design and management." FG-ML5G "will lead an intensive one-year investigation into where technical standardization could support emerging applications of machine learning in fields such as big data analytics, network management and orchestration, and security and data protection."

In addition, FG-ML5G will draft technical reports and specifications for machine learning for future networks, including interfaces, network architectures, protocols, algorithms and data formats. The ITU's announcement further says,

The Focus Group will consider machine-learning methods' compatibility with a wide variety of fixed and mobile communication stacks, encouraging the development of methods attuned to the operational requirements of the networking industry.

Interoperability is high on the agenda. The Focus Group will propose means to train, adapt, compress and exchange machine-learning algorithms. This work will promote the emergence of an ecosystem able to support the interaction of multiple machine-learning algorithms.

Machine-learning algorithms are helping operators to make smarter use of network-generated data. These algorithms enable ICT networks and their components to adapt their behavior autonomously in the interests of efficiency, security and optimal user experience.

My colleagues and I at ROI3 will collaborate with Alex Brooks of AE Brooks, LLC (d/b/a Entreprov) in our participation of FG-ML5G. Entreprov is a Seattle, Wash.-based company that helps small and medium-sized businesses increase their customer base and extend lifetime value of current customers through machine learning and business strategy. In his blog post about joining FG-ML5G, Mr. Brooks said, with Entreprov and ROI3 joining forces we have the opportunity to provide a unique perspective on how Machine Learning can impact 5G technology.

ROI3 previously participated on ITU's focus group to identify the network standardization requirements for the 5G development of International Mobile Telecommunications (IMT) for 2020 and beyond. The Focus Group on network aspects of IMT-2020 was established in May 2015 to analyze how emerging 5G technologies will interact in future networks as a preliminary study into the networking innovations required to support the development of 5G systems. The group took an ecosystem view of 5G research of development and published the analysis in a report to its parent group, ITU-T Study Group 13, in December 2016.

I am excited to have the opportunity to learn more about machine learning. In collaborating with Mr. Brooks on FG-ML5G, it is my hope to better understand the role of machine learning in fields such as big data analytics, network management and orchestration, and security and data protection on global scale.

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.

Microsoft Security Forum: Security in a Cloud-First, Mobile First World

Whether it was the convenience of accessing documents through any internet connection, easing the budgetary pressure of maintaining a private server or appreciating new technology, I was an early-adopter of Microsoft's cloud computing platform that debuted over ten years ago. As mobile applications have evolved and become readily available, I find myself using a smartphone to access my documents stored in the cloud more frequently. While conveniently accessing documents stored or apps hosted in the cloud is important, keeping the information secure is always paramount. Therefore, I did not hesitate to register for a mobile security forum, "Security in a Cloud-First, Mobile First World," Microsoft hosted on Oct. 10, 2017 in Bellevue, Wash.

Security for Your Digital Transformation

In his presentation, "Security for your digital transformation," Javier Dominguez, a Technical Solutions Professional at Microsoft, highlighted the four-step process Microsoft utilizes to secure its cloud computing platform: (1) identity and access management (protect users' identities & control access to valuable resources based on user risk level), (2) threat protection (protect against advanced threats and recover quickly when attacked), (3) information protection (ensure documents and emails are seen only by authorized people), and (4) security management (gain visibility and control over security tools).

He also noted that two billion records were compromised in 2016, which led to an average cost to a business of $15 million per breach (not including the reputation impact a business may experience when its data is compromised).

Identity & Access Management

Speaking during the second session, "Identity & Access Management," Mr. Dominguez said 81 percent of breaches are caused by credential theft, 73 percent of passwords are duplicates, and 80 percent of employees use non-approved apps. In securing its cloud platform, Microsoft asks the following questions about access control:

• Who is accessing? What is their role? Is the account compromised?
• Where is the user based? From where is the user signing in? Is the IP anonymous?
• Which app is being accessed? What is the business impact?
• Is the device healthy? Is it managed? Has it been in a botnet?
• What data is being accessed? Is it classified? Is it allowed off premises?

Mr. Dominguez also highlighted a new service called Windows Hello for Business, which replaces passwords with strong two-factor authentication on PCs and mobile devices. This authentication consists of a new type of user credential that is tied to a device and uses a biometric or PIN. In addition, Windows Hello for Business lets user authenticate to an Active Directory or Azure Active Directory account.

Protecting Against Modern Attacks

Speaking on protecting against modern attacks, Ken Malcolmson, an Executive Security Advisor at Microsoft, emphasized to the audience that cyber threats are a material risk to their business. He noted how Microsoft is detecting malicious activity in organization including (1) detecting compromised user credentials, (2) detecting malicious apps and data, (3) detecting advanced threats and abnormal behavior, and (4) detecting advance threats to hybrid workloads.

The objective with implementing multiple detecting mechanisms, Mr. Malcolmson said, is to "raise the cost of attack." In other words, increasing the time and financial resources required to compromise a cloud system will diminish a hacker's incentive.

Mr. Malcolmson then outlined five methods for responding to threats quickly:

1. Respond to Compromised Identities. Get recommendations and remediation actions in case of a suspicious activity on-premises or in the cloud; review next steps on a simple, actionable attack timeline; and identify threats before the attackers access critical data and resources.
2. Respond to Malicious Email Files. Remove emails found to be malicious after they land in user inbox; intelligent filters which update based on evolving cyber threat landscape; and ability to remediate for real-time malicious emails.
3. Respond to Compromised Data. Identify high-risk and anomalous usage in cross cloud apps - including Office 365 and get recommendations and remediation actions for next steps.
4. Respond to Compromised Devices. Remediate potential threats and prevent reoccurrence using built in technologies; receive mitigation guidance for remediation for threats and future risks; and assess organizational security score including trends over time.
5. Respond to Compromised Workloads Across Hybrid Infrastructure. Prioritized security alerts that help you respond quickly with azure security center; recommendations to mitigate threats and vulnerabilities; and threat intelligence reports for deeper insights into attack.

Information Protection

Mr. Dominguez then made a presentation on protecting and managing your data throughout its lifecycle noting that the "new world of work is driving change." Elaborating on this point, he provided some statistical data:

• 41 percent of of employees say mobile business apps change how they work;
• 85 percent of enterprise organizations keep sensitive information in the cloud;
• 88 percent of organizations no longer have confidence to detect and prevent loss of sensitive data; and
• 58 percent have accidentally sent sensitive information to the wrong person.

Mr. Dominguez discussed the lifecycle of a sensitive data including how data is created, imported, and modified across various locations:

• Data is detected across devices, cloud services, on-premises environments;
• Sensitive data is classified and labeled based on sensitivity, used for either protection policies or retention policies;
• Data is protected based on policy. Protection may in the form of encryption, permissions, visual markings, retention, deletion, or a DLP (data loss prevention) action such as blocking sharing;
• Data travels across various locations, shared protection is persistent, travels with the data;
• Data is monitored. Reporting on data sharing, usage, potential abuse; take action and remediate; and
• Retain, expire, delete data via data governance policies.

Microsoft Security Management

Making the forum's final presentation, Mr. Dominguez noted the different ways chief information security officers can secure their company's data including:

• Use Azure Active Directory to secure identities in your environment;
• Enable threat management for your devices through Windows Defender Security Center;
• Manage and control apps and data for your SaaS apps with Office 365 Security and Compliance Center as well as Microsoft Cloud App Security; and
• Consolidate security management for your infrastructure in cloud and on-premises with Azure Security Center.

I found value in the information presented during the security forum. As a customer of Microsoft's cloud computing platform, I appreciated getting a better understanding on how the company is protecting their customer's data against unauthorized access, detect attacks and breaches, and help with responding and adapting to prevent it from happening again.

While I am not a IT director/manager or security officer, per se, as an active user of cloud computing platforms for personal and business purposes, I understand the importance of cybersecurity and the financial and reputational impact a data breach can have to myself or my business.

How are you or your business using cloud computing? What methods are you using to secure your data?

Aaron Rose is an advisor to talented entrepreneurs and co-founder of great companies. He also serves as the editor of Solutions for a Sustainable World.