Some industry experts argue that machine learning (ML) will reverse an increasing trend toward passive investment funds. But although ML offers new tools that could help active investors outperform the indexes, it is unclear whether it will deliver a sustainable business model for active asset managers. Let's start with the positives A form of artificial intelligence, ML enables powerful algorithms to analyze large data sets in order make predictions against defined goals. Instead of precisely following instructions coded by humans, these algorithms self-adjust through a process of trial and error to produce increasingly more accurate prescriptions as more data comes in. ML is particularly adaptable to securities investing because the insights it garners can be acted on quickly and efficiently.

Two of the AI chip industry's most promising startups for enterprise computing, Graphcore and SambaNova, have raised additional funding this week. Each has its own approach to AI hardware. Both are competing to supply silicon for AI workloads in data centers. Both also have unicorn status -- that is, they are private companies valued at more than $1 billion. Graphcore Round D2 Graphcore, based in Bristol, UK, has raised $150 million in a D2 round in a bid to secure its position as a leading pure-play AI processor company. The company's previous funding round, series D, was completed at the end of 2018 and raised $200 million.

How Artificial Intelligence and Automation may reshape supply chain roles as we know them? Technological advancements throughout time have caused periods of huge change.

Graphcore Ltd., the British semiconductor firm whose chips are used to run artificial intelligence programs, has raised $150 million, bringing its valuation to $1.95 billion. The company now has $300 million in cash, which it will use to invest in research and development and global expansion, Bristol, England-based Graphcore said in a statement on Tuesday. After it raised $200 million in 2018, Graphcore was approached by additional investors who wanted to put money into the company, Chief Executive Officer Nigel Toon said in an interview. While the company has no immediate plans for an initial public offering, several of its investors, such as Baillie Gifford, have experience investing in publicly traded technology companies and are the types of shareholders the company would try to target if it were to go public at some point in the future, Toon said. "Having this additional capital on hand allows us to accelerate our investment and allows us to be in a position to support the really large customers who we're building business with," Toon said.

They beat us at chess and trivia, supplant jobs by the thousands, and are about to be let loose on highways and roads as chauffeurs and couriers. Now, fresh signs of robot supremacy are emerging on Wall Street in the form of machine stock analysts that make more profitable investment choices than humans. At least, that's the upshot of one of the first studies of the subject, whose preliminary results were released in January. Buy recommendations peddled by robo-analysts, which supposedly mimic what traditional equity research departments do but faster and at lower costs, outperform their flesh-and-blood counterparts over the long run, according to Indiana University professors. "Using this type of technology to make investment recommendations or to conduct investment analyses is going to become increasingly important," Kenneth Merkley, an associate professor of accounting and one of the authors, said by phone.

Adesto Technologies Corporation IOTS fourth-quarter 2019 results are expected to benefit from strong demand for the company's IOT related offerings. For the quarter, the company expects revenues in the range of $32-$35 million. The Zacks Consensus Estimate for revenues is currently pegged at $33.6 million, indicating growth of 19.5% from the year-ago quarter. The consensus mark for fourth-quarter earnings has been steady at 4 cents over the past 30 days. The company had reported loss of 4 cents in the year-ago reported quarter.

They beat us at chess and trivia, supplant jobs by the thousands, and are about to be let loose on highways and roads as chauffeurs and couriers. Now, fresh signs of robot supremacy are emerging on Wall Street in the form of machine stock analysts that make more profitable investment choices than humans. At least that's the upshot of one of the first studies of the subject, whose preliminary results were released in January. Buy recommendations peddled by robo-analysts, which supposedly mimic what traditional equity research departments do but faster and at lower cost, outperform their flesh-and-blood counterparts over the long run, according to Indiana University professors. "Using this type of technology to make investment recommendations or to conduct investment analyses is going to become increasingly important," Kenneth Merkley, an associate professor of accounting and one of the authors, said by phone.

Last year, Ted Serbinski called his accelerator, Techstars Detroit, the "'comeback city's' startup ecosystem." Since 2015, the accelerator had supported and mentored 54 transportation-related companies, with funding from some big transportation names, like Ford, Honda, AAA, and Nationwide. Success stories included Cargo, a startup that helps ride-hail drivers make supplemental income by running rider-friendly "convenience stores" out of their cars; Splt, a ride-share company acquired by Bosch in 2018; and Acerta, which applies machine learning to automotive manufacturing. Instead, it's shutting down, as earlier reported by TechCrunch. "Right now, there is no funding," says Serbinski, the accelerator's managing director.

Your IT service management platform and related tools are the workhorses and frameworks of operating any kind of successful IT organization, providing a way to track work, prioritize tasks, and make sure user issues get solved. It may not be the most glamorous technology in your organization's tech stack, but it gets the job done. Yet today even ITSM and related tools and platforms are poised to change in a significant way -- driven by the data revolution. "IT is where digital transformation begins, and we are a powerful strategic partner for CIOs all over the world," said Bill McDermott, in his first earnings call on January 29 as CEO of ServiceNow, which provides ITSM and other tools and frameworks to the IT industry. McDermott joined ServiceNow in October 2019 from SAP where he also served as CEO.

SAN FRANCISCO, Feb. 04, 2020 (GLOBE NEWSWIRE) -- Labelbox, the leading training data platform for enterprise machine learning applications, today announced the close of a $25 million Series B funding round led by Andreessen Horowitz with General Partner Peter Levine joining the Labelbox board of directors. Previous investors First Round Capital, Gradient Ventures (Google's AI-focused venture fund) and Kleiner Perkins also participated. To date, Labelbox has raised $39 million in venture funding. Labelbox offers a training data platform for machine learning teams to build real-world artificial intelligence. The platform consists of label editor tools, batch & real-time labeling workflows, collaboration, quality review, analytics, and an optional, fully managed and dedicated labeling workforce.