Alteryx, a data management vendor founded in 1997 and based in Irvine, Calif., unveiled its latest platform update in a blog post on Sept. 1, and all of the features included in the release are now generally available to customers. Alteryx previously offered data modeling capabilities with its Assisted Modeling Tool, but new in Alteryx 2020.3 is Automatic Mode within the tool. With a single click of a mouse, users can create a machine learning pipeline that automatically determines the best algorithms, data features and data transformations to create a data model. By adding Automatic Mode, Alteryx is targeting users without a background in data science in addition to data experts already enabled by the Assisted Modeling Tool, according to Dave Menninger, research director of data and analytics research at Ventana Research. "They've adopted a position that you will have data science experts and people who are dabbling in data science, and they've done a good job creating a single platform that those two audiences can share," he said.
Those deemed in the higher class may be envied for their luxurious cars, large homes and stylish clothes, but there is one thing they do not have – the ability to read people's emotions. A study used a cognitive empathy test called'the Reading the mind in the eyes,' which participants from higher and lower social classes were asked to determine emotional states from images of eyes. The results showed those in the lower class were better at understanding other people's minds compared to their counterparts. Experts suggest the reason is because lower social classes tend to prioritize the needs and preferences of others, and are ultimately more empathetic. A study used a cognitive empathy test called'the Reading the mind in the eyes,' which participants from higher and lower social classes were asked to determine emotional states from images of eyes - and the team calculated the scores The study was conducted by a team at the University of California, Irvine who questioned – 'How does access to resources (e.g., money, education) influence the way we process information about other human beings,' PsyPost reported.
Syntiant Corp., the "neural decision processor" startup, announced completion of another funding round this week along with the shipment of more than 1 million low-power edge AI chips. The three-year-old startup based in Irvine, Calif., said Tuesday (Aug. The round was led by Microsoft's (NASDAQ: MSFT) venture arm M12 and Applied Ventures, the investment fund of Applied Materials (NASDAQ: AMAT). New investors included Atlantic Bridge Capital, Alpha Edison and Miramar Digital Ventures. Intel Capital was an early backer of Syntiant, part of a package of investments the chip maker announced in 2018 targeting AI processors that promise to accelerate the transition of machine learning from the cloud to edge devices.
Syntiant, a startup developing AI edge hardware for voice and sensor solutions, today closed a $35 million round. CEO Kurt Busch says the funds will be used to ramp up production throughout the remainder of 2020. According to a report published by Meticulous Research, the speech and voice recognition hardware market is expected to reach $26.8 billion by 2025. That's because devices like smart speakers, smart displays, phones, headphones, hearing aids, and laptops require low-power chips to process utterances. While some system-on-chip offerings sport coprocessors to handle voice recognition, they're often not able to accommodate multiple form factors. Three-year-old Syntiant, which is headquartered in Irvine, California, provides hardware that merges machine learning with semiconductor design for always-on voice applications.
Ultra-low-power AI accelerator startup Syntiant has raised another $35 million in a series C round of funding to bring the total raised by the company to $65 million. Syntiant, whose 66 staff work out of Irvine, Calif., also announced that it has hit a shipping milestone with 1 million parts in the hands of customers. Third round Syntiant's C round was led by Microsoft's VC fund, M12, and Applied Ventures, the VC arm of Applied Materials. "[$35m] gets us pretty far into growing our sales team and ramping our revenue," Syntiant CEO Kurt Busch told EE Times. "We have the second-generation chip already back in the lab, which we expect to announce before the end of the year… this funding will also be used to fund development of third generation silicon and build out our customer base."
Employees at Blizzard Entertainment, a division of Activision Blizzard Inc., began circulating a spreadsheet on Friday to anonymously share salaries and recent pay increases, the latest example of rising tension in the video game industry over wage disparities and executive compensation. Blizzard, based in Irvine, California, makes popular games including Diablo and World of Warcraft. In 2019, after an internal survey revealed that more than half of Blizzard workers were unhappy with their compensation, the company told staff it would perform a study to ensure fair pay, according to people familiar with the situation. Blizzard implemented the results of that study last month, which led to an outcry on the company's internal Slack messaging boards. One employee then created a spreadsheet and encouraged staff to share their compensation information.
Amazon is rolling out its robot delivery trial to more cities. The e-commerce giant launched its delivery system, Amazon Scout, in January 2019 using electric, autonomous vehicles that can navigate sidewalks to deliver packages. They were first developed and tested in Snohomish County, north of Seattle, then rolled out in Irvine, California in August of that year. Now, Amazon will extend that trial to select customers in Atlanta, Georgia, and Franklin, Tennessee. In a blog post Tuesday, Sean Scott, vice president of Amazon Scout, said the service was most recently used to help meet customer demand in the trial areas during the pandemic, in conjunction with its existing fleet of delivery vehicles.
Organizers of the 58th Annual Meeting of the Association for Computational Linguistics (ACL) today announced their Best Paper Awards, with the Best Overall Paper going to Beyond Accuracy: Behavioral Testing of NLP Models with CheckList by researchers from Microsoft, University of Washington, and University of California-Irvine. The winning paper introduces CheckList, a task-agnostic methodology for testing NLP models that includes a matrix of general linguistic capabilities and test types that facilitate comprehensive test ideation, and a software tool that can quickly generate a large number of diverse test cases. ACL announced two Honourable Mentions in the Overall Best Paper category: Don't Stop Pretraining: Adapt Language Models to Domains and Tasks by researchers from the Allen Institute for Artificial Intelligence and University of Washington. The honourable mentions are Don't Stop Pretraining: Adapt Language Models to Domains and Tasks by researchers from the Allen Institute for Artificial Intelligence and University of Washington; and Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics by researchers from the University of Melbourne. The ACL 2020 Test-of-Time Awards meanwhile went to the 1995 papers Centering: A Framework for Modeling the Local Coherence of Discourse by Barbara J. Grosz, Aravind K. Joshi, and Scott Weinstein; and Unsupervised Word Sense Disambiguation Rivaling Supervised Methodsby David Yarowsky; and the 2010 papers Distributional Memory: A General Framework for Corpus-based Semantics by Marco Baroni and Alessandro Lenci; and Word Representations: A Simple and General Method for Semi-supervised Learning by Joseph Turian, Lev-Arie Ratinov, and Yoshua Bengio.
The solution to online hate speech seems so simple: Delete harmful content, rinse, repeat. But David Kaye, a law professor at the University of California, Irvine, and the U.N. special rapporteur on freedom of expression, says that while laws to regulate hate speech might seem promising, they often aren't that effective--and, perhaps worse, they can set dangerous precedents. This is why France's new social media law, which follows in Germany's footsteps, is controversial across the political spectrum there and abroad. On May 13, France passed "Lutte contre la haine sur internet" ("Fighting hate on the internet"), a law that requires social media platforms to rapidly take down hateful content. Comments that are discriminatory--based on race, gender, disability, sexual orientation, and religion--or sexually abusive have to be removed within 24 hours of being flagged by users.