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Element AI Closes Series B – Raises $151 Million To Bring AI To More Companies

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Element AI Closes Series B - Raises $151 Million To Bring AI To More Companies

The Canadian startup Element AI, based out of Montreal, has recently completed its series B round of funding, raising $151 million dollars to fund their AI expansion goals. Element AI’s goal is to bring the power of AI to companies that aren’t typically likely to use it, making AI available to those who aren’t savvy regarding AI and computer technologies.

Element AI was founded in 2016, and it aims to dramatically expand the use of AI outside of the traditional fields like retail and security. Element AI hopes to “turn research and industry expertise into software solutions that exponentially learn and improve”, focusing specifically on the supply chain and financial services sectors.

According to VentureBeat, Element AI’s successful series B funding managed to accrue over $151.3 million dollars from both old and new investors. The startup plans to invest this money in the marketing of its current product line as well as in the development of new AI solutions.  The CEO of Element AI, Jean-François Gagné, put out a recent press release remarking that the company is excited to start working with their new partners who wish to explore the potential of AI in non-traditional market areas. According to Gagné, Element AI remains fully committed to operationalizing AI, despite it being “the industry’s toughest challenge”.

Although AI is frequently in the headlines, AI applications are primarily found in a few specific fields. Element AI was founded with the idea that AI will be the next major transformative technology, although not every business is equipped to take advantage of it. The disparity between technology companies that are positioned to take advantage of AI and non-tech companies creates a substantial divide between companies who can use AI and those that can’t. Element AI wants to bring AI algorithms to companies that lack the experience to properly utilize AI.

Element AI set out to achieve this by providing consultation to companies that could potentially benefit from utilizing AI, helping them identify areas where they could implement AI solutions. The company has since expanded to offering other services, offering products tailored to specific industries like retail/logistics, financial services, manufacturing, and insurance. The list of specialized products that the company offers is likely to grow, thanks to the substantial increase in funding the company has received.

Element AI is not the only company to try and operationalize AI, with other companies like UiPath creating tools designed to allow companies to automate repetitive tasks. However, Element has definitely been the most successful at bringing AI to a wider section of society.

As reported by CrunchBase, Element AI has worked with many different companies, including Gore Mutual, Bank of Canada, National Bank, LG, and others. In terms of investors, many of their supporters from the series A investment have returned to back the company a second time, including Real Venture, BDC Capital, Hanwha Asset Management and DCVC. Some of the new investors in the company include Gouvernement du Quebec and McKinsey & Company.

According to TechCrunch, McKinsey is a management consultancy company, and though at first glance the company seems like a competitor to Element AI, McKinsey seems to be funneling customers to Element. Many system integrators don’t have the experience with AI needed to ascertain the best uses for the technology, while Element AI has experience with emerging technologies and computing. QuantumBlack, the AI and advanced analytics division of McKinsey, has also established its own offices in Montreal, where they will be collaborating on projects with Element AI.

Element AI also stated in its press release that the company would be using the newly acquired funds to expand its operations across the globe. Currently, the company has approximately 500 employees located in offices around Singapore, South Korea, Seoul, London, and Toronto.

Element AI isn’t the only Canadian AI startup to see recent success. The company CDPQ recently launched its own AI funding initiative intended to advance the commercialization of AI platforms throughout Quebec.

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Sony Establishes A New Sony Artificial Intelligence Global Division

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Sony Establishes A New Sony Artificial Intelligence Global Division

Online portals like Slashgear and others have brought the news that tech giant Sony is launching a new global division which will have its focus on developing artificial intelligence, The goal is to apply MA through gaming, photography and even cooking. It is planned that the new division will have offices throughout the world. As reported, Hiroaki Kitano, President, and CEO of Sony Computer Science Laboratories will be the global head of Sony AI. Peter Stone will be the US chief, a computer science researcher with a storied background in Reinforcement Learning and Robotics.

The news coincides with Sony’s official press release about the research agreement the company signed with Carnegie Mellon University (CMU) on joint work to develop AI and robotics. Their initial efforts will focus on cooking and delivery.

Already trying to strengthen their AI-development efforts, Sony has brought back  Aibo robotic dog with the new version set to take “full advantage of things like cloud processing, facial recognition, and learning AI’s to make the pup more realistic and engaging.” While Aibo development on the surface might seem like “ fairly playful interpretation of artificial intelligence,” Sony’s purpose behind the toy’s development is to explore  “how such technologies can ‘unleash human imagination and creativity with AI,’ tapping into all of the company’s different divisions in the process. It’ll also look beyond Sony’s existing businesses, to figure out new potential applications.”

Using this as a stepping stone, Sony’s teams in Japan, the US, and Europe plan to launch “three flagship projects’” one of which is the aforementioned gastronomy research with CMU. The other two planned fields are gaming and imaging&sensing.

Sony points out that it is focusing on gaming as games are widely used in AI experiments, and “and game worlds are a commonly implemented research method to develop artificial intelligence.’ Of course, there is a more direct application on Sony products as the new AI teams could “help the PlayStation team develop smarter in-game characters.”

For imaging and sensing, Sony aims to produce new types of sensors that can be used as “sense organs” for artificial intelligence. “In that case, we can consider AI systems in a wide variety of scenarios, from real-time data analysis to robots, to agents within a server space. Each of those scenarios has different requirements in terms of processing time or level of input necessary.” In that field, as Endgadget notes, Sony has already made strides in products like the A6600 camera, where it contributes to an impressive improvement in autofocus.

Discussing its plans to develop the AI-use in gastronomy, Sony says that it intends to “harness AI and robotics from the perspective of “getting closer to creators,” and with the aim of expanding the creative options/creativity of chefs. Top-level chefs can gain inspiration for new recipes by interacting with AI, and we also want to help all of those who prepare food in their day to day lives to enjoy that process of creation even more.”

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Microsoft Partners with Startup Graphcore to Develop AI Chips

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Microsoft Partners with Startup Graphcore to Develop AI Chips

Microsoft hopes that its Azure cloud platform will catch up in popularity with Amazon and Google, so as Wired reports, it has partnered with a British startup Graphcore to come up with a new computer chip that would be able to sustain all-new artificial intelligence developments.

As Wired notes, Bristo, UK startup Graphcore “has attracted considerable attention among AI researchers—and several hundred million dollars in investment—on the promise that its chips will accelerate the computations required to make AI work.” Since its inception in 2016, this is the first time that the company is publicly coming up with its chips and testing results.

Microsoft’s invested in Graphcore in December 2018 “as a part of a $200 million funding round”, as it wants to stimulate the use of its cloud services to a growing number of customers that use AI applications.

Graphcore itself designed its chips from scratch “to support the calculations that help machines to recognize facesunderstand speechparse languagedrive cars, and train robots.” The company expects that its chips will be used by “companies running business-critical operations on AI, such as self-driving car startups, trading firms, and operations that process large quantities of video and audio, as well as those working on next-generation AI algorithms.”

According to the benchmarks published by Microsoft and Graphcore on November 13, 2019, “the chip matches or exceeds the performance of the top AI chips from Nvidia and Google using algorithms written for those rival platforms. Code is written specifically for Graphcore’s hardware maybe even more efficient.”

The two companies also stated that “certain image-processing tasks work many times faster on Graphcore’s chips,” and that “ they were able to train a popular AI model for language processing, called BERT, at rates matching those of any other existing hardware.”

Moor Insights AI chip specialist Karl Freund is of the opinion that the results of the new chip show that it is “cutting-edge but still flexible,”  and that “they’ve done a good job making it programmable,” an extremely hard thing to do.

Wired further adds that Nigel Toon, co-founder, and CEO of Graphcore, says the companies began working together a year after his company’s launch, through Microsoft Research Cambridge in the UK. He also told the publication that his company’s chips are especially well-suited to tasks that involve very large AI models or temporal data. Also, one customer in finance supposedly saw a 26-fold performance boost in an algorithm used to analyze market data thanks to Graphcore’s hardware.

Some other, smaller companies used this occasion to announce that “they are working with Graphcore chips through Azure.” This includes Citadel, which will use the chips to analyze financial data, and Qwant, a European search engine that wants the hardware to run an image-recognition algorithm known as ResNext.

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Senators Began To Get Involved In AI

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Senators Began To Get Involved In AI

According to the top Democrat in the U.S. Senate, Senator Chuck Schumer (D-NY), the U.S. government should make a massive investment in artificial intelligence. He is advocating for the government to create a brand new agency to invest $100 billion in basic research in AI over 5 years. According to the senator, this will help the United States compete against Russia and China, who are moving ahead quickly in the field. The agency will also provide funding to certain areas where U.S. companies are not heavily involved. 

Senator Schumer gave a speech last week to senior national security and research policy-makers who gathered in Washington D.C. It was the first time he publicly outlined the new plan, and he is in an influential position to make progress as minority leader. This comes at a time when there is an increasing level of interest in AI and other related fields including robotics. There has also been a recent presidential executive order.

The new national science tech fund would invest $100 billion into “fundamental research related to AI and some other cutting-edge areas.”

Some of those cutting edge areas include quantum computing, 5G networks, robotics, cybersecurity, and biotechnology. The money would be used to fund research at U.S. universities, companies, and other federal agencies. It would also fund “testbed facilities” used to complete work needed to turn discoveries into commercial products. 

Behind Closed Doors

This plan has been discussed behind closed doors for several months by tech industry executives and academic leaders, but it still has a long way to go. According to Schumer, “this is just a discussion draft.”

Schumer suggested the fund would be a “subsidiary” of the National Science Foundation (NSF). It would also have a connection to the Defense Advanced Research Projects Agency (DARPA) within the Department of Defense (DOD) and have a board of directors. 

National Security Commission on Artificial Intelligence

The speech took place at a symposium sponsored by the National Security Commission on Artificial Intelligence, which is a bipartisan body that was created by Congress. This issue can bring together politicians from both parties, especially during a time when the government is so divided over the impeachment proceedings taking place against President Donald Trump. 

“This should not be a partisan issue. This is about the future of America,” Schumer asserted, saying the country’s security and economic prosperity depend on making such a major investment. And he asked the politically well-connected audience to help him sell the proposal.

“This idea has support from some people very close to the president and very close to [Senate Majority Leader] Mitch McConnell [R],” Schumer said. “But thus far they have been unable to get their [principals’] full-throated support. Anyone here who has any relationship with those people or people near them should be pushing this.”

The U.S. Government 

The U.S. government has not been completely absent from artificial intelligence, but many believe more needs to be done to keep pace with technology which will revolutionize almost everything.

Last month, the Department of Energy released plans to request $3 billion to $4 billion from Congress over the next 10 years. It will be used for AI research which already has some investment taking place. NSF officials have said that the agency spends that amount each year over the past decade in order to improve AI algorithms and software. 

Trump issued an executive order in February that told NSF, DOD, and other federal agencies to invest more in high-performance computing. Under the order, federal agencies are required to develop an “action plan to protect the U.S. advantage in AI technology.”

 

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