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Economic revitalization minister Daishiro Yamagiwa on Sunday revealed a plan to set up a fund to support the development of cutting-edge technologies crucial for the country's economic security. "The government will fully support private-sector companies' research and development activities for advanced technologies, and their efforts to prepare a business environment for such technologies," he said during a television program. The fund will likely be worth about ¥100 billion. The government will include the planned fund in a package of economic measures to be drawn up after the Oct. 31 Lower House election. The fund is expected to help Japanese companies and universities develop artificial intelligence, quantum and robot technologies, biotechnology and other important tech, and put them into practical use.
Just when you thought it couldn't grow any more explosively, the data/AI landscape just did: the rapid pace of company creation, exciting new product and project launches, a deluge of VC financings, unicorn creation, IPOs, etc. It has also been a year of multiple threads and stories intertwining. One story has been the maturation of the ecosystem, with market leaders reaching large scale and ramping up their ambitions for global market domination, in particular through increasingly broad product offerings. Some of those companies, such as Snowflake, have been thriving in public markets (see our MAD Public Company Index), and a number of others (Databricks, Dataiku, DataRobot, etc.) have raised very large (or in the case of Databricks, gigantic) rounds at multi-billion valuations and are knocking on the IPO door (see our Emerging MAD company Index). But at the other end of the spectrum, this year has also seen the rapid emergence of a whole new generation of data and ML startups. Whether they were founded a few years or a few months ago, many experienced a growth spurt in the past year or so. Part of it is due to a rabid VC funding environment and part of it, more fundamentally, is due to inflection points in the market. In the past year, there's been less headline-grabbing discussion of futuristic applications of AI (self-driving vehicles, etc.), and a bit less AI hype as a result. Regardless, data and ML/AI-driven application companies have continued to thrive, particularly those focused on enterprise use trend cases. Meanwhile, a lot of the action has been happening behind the scenes on the data and ML infrastructure side, with entirely new categories (data observability, reverse ETL, metrics stores, etc.) appearing or drastically accelerating. To keep track of this evolution, this is our eighth annual landscape and "state of the union" of the data and AI ecosystem -- coauthored this year with my FirstMark colleague John Wu. (For anyone interested, here are the prior versions: 2012, 2014, 2016, 2017, 2018, 2019: Part I and Part II, and 2020.) For those who have remarked over the years how insanely busy the chart is, you'll love our new acronym: Machine learning, Artificial intelligence, and Data (MAD) -- this is now officially the MAD landscape! We've learned over the years that those posts are read by a broad group of people, so we have tried to provide a little bit for everyone -- a macro view that will hopefully be interesting and approachable to most, and then a slightly more granular overview of trends in data infrastructure and ML/AI for people with a deeper familiarity with the industry. Let's start with a high-level view of the market. As the number of companies in the space keeps increasing every year, the inevitable questions are: Why is this happening? How long can it keep going?
Key Takeaways: - New Artificial Intelligence (AI) technology is being integrated into all industries. I have written a few articles regarding the liability of autonomous systems under the United Arab Emirates' (UAE) law, regarding the liability of autonomous systems under the UAE's Civil Code, available remedies, comparing to other regimes, and recommendations for law, policy and ethics. I focused mainly on the liability and regulation of autonomous or Artificial Intelligence (AI) systems under the laws of the UAE, but I also compared the UAE's legal system to other regimes, including the United Kingdom (UK) and the European Union (EU). I concluded that generally speaking, when it comes to AI, the issues are similar across the globe. In the near future, every single one of us will be dealing in some shape or form with an autonomous system or an AI-powered system.
Jordan Lemos, a writer for video games, has lived in three different cities over the past five years. He moved from Los Angeles to Quebec to Seattle -- working on blockbusters such as Assassin's Creed Odyssey and Ghost of Tsushima -- because the jobs required it. So when he was looking for a new gig last year, he told prospective employers he wasn't going to do it again. He would only work remotely. Several big game companies were quick to say no once they heard his ultimatum.
This blog post has been co-authored by Slawek Kierner, SVP of Enterprise Data & Analytics, Humana and Tie-Yan Liu, Assistant Managing Director, Microsoft Research China. Trips to the hospital happen. And while everyone in the industry strives to deliver world-class care for in-patient experiences, everyone--patients and care teams alike, would prefer to avoid those stays at the hospital. The teams at Humana believed they had enough data to explore the possibility of proactively identifying when patients were heading toward a high-risk event, and they put Microsoft Cloud for Healthcare and AI technology to the test. Humana's questions were straightforward: How do we take the data we have today and use it proactively?
China's startup ecosystem, which produced several world-leading companies, has been in the news in the recent past about the impact of the government regulations on the big technology firms. However, despite the regulatory shakeups and the COVID-19 pandemic notwithstanding, China has emerged as a powerhouse for artificial intelligence (AI) unicorns, according to Thematic Research at GlobalData, a leading data, and analytics company. GlobalData's research shows that of the total of 45 AI unicorns globally, China has the biggest share with 19 unicorns headquartered in the country. These 19 unicorns are collectively valued at $43.5bn. Priya Toppo, Analyst of Thematic Research at GlobalData, comments: "China is a leading player in AI, with a number of established companies such as Baidu, Hikvision, iFlytek, Tencent, and Alibaba. The country also has a strong AI startup ecosystem, which is evident from the large number of AI unicorns (privately held startup valued at $1bn or more)."
For the last couple of years the coronavirus has been teaching a master class on exponential growth: from January 2020, when 100 cases in China led the WHO to call a public health emergency, to today, when there have been over 239 million cases worldwide. Before that, as people have begun to forget, exponential growth was perhaps best known as the secret behind the rise of computers. Moore's Law -- the observation made by Intel co-founder Gordon Moore that the number of transistors on an integrated chip doubles roughly every two years -- is the reason the smartphone in your pocket is more than a thousand times more powerful than the biggest computers 50 years ago, which only governments and large organisations could afford. The exponential growth of computer power led the inventor Ray Kurzweil to propose the Law of Accelerating Returns and predict that by 2045 machine intelligence will pass that of humans -- a.k.a. the Singularity. In Exponential: How Accelerating Technology is Leaving Us Behind and What to Do About It, Azeem Azhar begins with the perception that Kurzweil's take was too narrow and that exponential growth is taking place in no less than four converging sectors: computing, energy, biology, and manufacturing.
PLEASANTON CA, Sept. 30, 2021 (GLOBE NEWSWIRE) -- The latest study titled "Global Artificial Intelligence in Manufacturing Market Ecosystem By Components; By Deployment; By Technology; By Application; By Device; By Region; By End Users (Logistics, Healthcare, Automotive, Retail, BFSI, Defence, Aerospace, Oil & Gas, Others) Forecast by 2027" published by AllTheResearch, features an analysis of the current and future scenario of the global Artificial Intelligence (AI) in Manufacturing Market. The Global Artificial Intelligence (AI) in Manufacturing Market was valued at USD 2.1 Bn in 2020 and is expected to reach USD 11.5 Bn by 2027, with a growing CAGR of 27.2% during the forecast period. The Artificial Intelligence in manufacturing market is forecasted to grow at a high rate owing to the accelerating innovations in industrial IoT and automation. The manufacturing industry is expected to be among the market leader in the artificial intelligence market. Further, the manufacturing industry is also expected to display the fastest growth during the forecast period due to rapid digital transformation to promote smart solutions in factories, logistics and management.
In its quest to drive the adoption of artificial intelligence (AI) across the country, multi-ethnic Singapore needs to take special care navigating its use in some areas, specifically, law enforcement and crime prevention. It should further foster its belief that trust is crucial for citizens to be comfortable with AI, along with the recognition that doing so will require nurturing public trust across different aspects within its society. It must have been at least two decades ago now when I attended a media briefing, during which an executive was demonstrating the company's latest speech recognition software. As most demos went, no matter how much you prepared for it, things would go desperately wrong. Her voice-directed commands often were wrongly executed and several spoken words in every sentence were inaccurately translated into text.
For residents of Kosuge, an idyllic village nestled in a valley deep in the mountains of Yamanashi Prefecture, fast food is a luxury. There aren't any convenience stores or supermarkets in the tiny community, let alone a McDonald's. So when Aeronext Inc. celebrated its 100th on-demand drone delivery in Kosuge in July, the startup treated villagers to fast food chain Yoshinoya Co.'s signature gyūdon beef bowls -- steamed rice topped with thinly sliced beef and simmered onions. Amid a small crowd of curious onlookers, hot meals prepared in a Yoshinoya kitchen car were hauled onto spider-like drones that took off in regular intervals to several drop-off stations dotted around the village. For those who got to savor the dish, it was a taste of the city delivered by air, and a glimpse of a future in which these flying devices could become an essential part of rural life.