Alteryx, a publicly traded analytics company, announced this morning that it has acquired Feature Labs, a machine learning startup that launched out of MIT in 2018. The company did not reveal the terms of the deal. Co-founder and CEO Max Kanter told TechCrunch at the time of the launch the company had been based on research at MIT that looked at how to automate the creation of machine learning algorithms. "Feature Labs is unique because we automate feature engineering, which is the process of using domain knowledge to extract new variables from raw data that make machine learning algorithms work," Kantor told TechCrunch in 2018. It is precisely this capability that appealed to Alteryx .

After 11 autopilot engineers left Tesla Inc (NASDAQ: TSLA) in May amid department restructuring, Tesla found itself in need of new software talent. On October 1, Tesla announced its acquisition of Deepscale, a Silicon Valley, California-based startup that will help actualize Tesla CEO Elon Musk's desire for its vehicles to become self-driving robotaxis. On LinkedIn, Deepscale's CEO Forrest Iandola announced his new role as a senior staff machine learning scientist at Tesla. CNBC reported that Tesla bought Deepscale "outright," but no financial details have surfaced. Deepscale is Tesla's sixth acquisition, including Maxwell Technologies in May 2019.

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The AIBC is an Artificial Intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an ecosystem layer. The AIBC implements a two-consensus scheme to enforce upper-layer economic policies and achieve fundamental layer performance and robustness: the DPoEV incentive consensus on the application and resource layers, and the DABFT distributed consensus on the fundamental layer. The DABFT uses deep learning techniques to predict and select the most suitable BFT algorithm in order to achieve the best balance of performance, robustness, and security. The DPoEV uses the knowledge map algorithm to accurately assess the economic value of digital assets.

The demand for artificial intelligence has grown significantly in the last few years due to the advantages it provides. Rising use of big data, growing demand for greater transparency and visibility into supply chain data and processes, and increasing adoption of AI for improving consumer services and satisfaction are some of the other factors driving the demand in this market. Moreover, growing applicability of AI in various industries has further augmented the demand in this market. The global artificial intelligence in supply chain market could be classified on basis of technology, application, end-user industry, and offerings. The end-user industry category can further be segmented into manufacturing, aerospace, automotive, retail, consumer packaged goods, healthcare, food and beverages, and others.

Montreal-based Element AI, which develops artificial intelligence-powered software solutions, announced this morning it has raised US$151.4 million in a massive Series B round. Founded in 2016 by a team of six partners including serial entrepreneurs Jean-François (JF) Gagné and A.M. Turing Award winner Yoshua Bengio, Element AI is described by lead investor Caisse de dépôt et placement du Québec (CDPQ) as "a company with a commercial focus that anticipates and creates AI products to address clients' needs." In its own words, Element AI "turns research and industry expertise into software solutions that exponentially learn and improve" and are adapted to specific industries with a primary focus on the financial services and supply chain sectors. Its offering, which includes advisory services, AI-enablement tools and products, aims to help large organizations "operationalize AI and create real business impact." Customers include LG and National Bank, among others.

Blackberry and Jaguar Land Rover have announced that they will work together to develop new autonomous vehicles using artificial intelligence (AI) and machine learning technologies. The two companies will use Blackberry's QNX operating system and Blackberry Cylance to develop a range of capabilities to bolster vehicle safety, including predictive software maintenance and cyber threat protection, in Jaguar Land Rover's next-generation vehicle architecture. Under the partnership, Blackberry will also help Jaguar Land Rover identify potential security vulnerabilities found in connected and autonomous vehicles. "BlackBerry is a trusted partner of the automotive industry because of our heritage and innovations in secure communications," Blackberry CEO John Chen said. "We are pleased to be Jaguar Land Rover's chosen partner for safety-certified technology, as we advance Artificial Intelligence and Machine Learning technologies to transform automotive safety."

Daisy Intelligence announced that it has raised $10 million (CDN) in Series A financing led by Framework Venture Partners and partnered by European-based corporate investor, Sonae IM. The funding will enable Daisy to expand globally, invest in sales and marketing, provide further support for its customer success teams, and expand its operational infrastructure as growth demands. Daisy's AI-powered technology platform helps retailers and insurance companies generate significantly improved financial results by delivering business recommendations and automating complex processes beyond human capability.Daisy is driving a revolution in retail with its core AI SaaS platform, adding intelligence and automation to merchandising decisions. Daisy has helped its retail clients increase year over year, same store sales an average of 2.9% by optimizing their promotional product and pricing mix. Insurance companies use Daisy's AI-powered risk management platform to detect and avoid millions of dollars in fraud and automatically adjudicate claims.

FarmWise announced today that it has raised a $14.5 million Series A round of funding for its autonomous agriculture robots. The round was led by Calibrate Ventures with participation from Wilbur Ellis, Xplorer Capital and Alumni Ventures Group. This brings the total amount raised by FarmWise to $20.2 million. Farmwise builds self-driving robots that use a combination of computer vision and AI to identify weeds among crops and precision mechanical tools to remove them without the need for herbicides. According to the press release sent to The Spoon, FarmWise says its robots have removed weeds from more than 10 million plants.

Bengaluru-based parent-tech startup Parentof has raised $1 million in a seed funding round to evolve its technology and expand its partner network. The recent funding round was led by angel investors V Srinivas and other existing investors. Founded in 2015, Parentof is a decision sciences organization that provides insights into child growth and decision analytics. The company creates an ecosystem for parents to easily access technology-enabled solutions to help drive better outcomes for children. It believes that applying research and technologies like Artificial Intelligence and Machine Learning can bridge the gap between the realities and assumptions of parenting.