As the IBM Watson experience shows, the path to AI success is fraught with challenges. Yet overall, it has been a very good year for AI and the companies developing it. So much so that Alphabet CEO Sundar Pichai, in a recent podcast recorded by BBC, says: “I view [AI] as a very profound enabling technology. If you think about fire or electricity or the internet, it is like that, but I think even more profound.”That profound impact is becoming more pronounced as AI is showing up in more industries, ranging from semiconductor design to software development to voiceovers, farming, distribution, music creation, and even classical sculpting. In all instances, AI is augmenting and possibly replacing human activities while dramatically speeding up development of the final product. In biology, determining the structure of just one protein can take years of laboratory work, but new AI released to the public by the University of Washington can reduce this time to as little as 10 minutes. In the sculpture example, a replica of “Psyche Revived by Cupid’s Kiss,” produced by ABB2, an industrial robot developed by ABB Robotics, required just over 11 days to produce, while the original by 18th-century sculptor Canova required roughly five years. And due to the pandemic, demand for industrial robots has surged in the last year across many industries.

InVia Robotics, an industrial robotics company based in Los Angeles, California, today announced it has raised $30 million in a series C round co-led by Microsoft’s M12 Ventures and Qualcomm, with participation from Hitachi. InVia says the new equity funding will be used to support its growth, specifically through adopting Qualcomm’s Robotics RB5 Platform and drawing on AI expertise from Hitachi and Microsoft.Companies are increasingly determined to improve warehouse automation in light of pandemic-related supply chain challenges. A recent Honeywell survey found that 14% of enterprises rank improving automation within their facilities as a top priority, while 37% rank it among their top three near-term goals. A separate report published in Forbes found that 96% of warehouse executives expect the warehouse automation value proposition to increase over the next three years.

Google’s parent Alphabet has spun out a new industrial robotics company called Intrinsic.Led by Wendy Tan-White, a veteran entrepreneur and investor who has served as VP of “moonshots” at Alphabet’s R&D business X since 2019, Intrinsic is setting out to “unlock the creative and economic potential” of the $42 billion industrial robotics market. The company said that it’s creating “software tools” to make industrial robots more affordable and easier to use, extending their utility beyond big businesses and to more people — at present 70% of the world’s manufacturing takes place in just 10 countries.Industrial robots have surged in demand over the past year as businesses have scrambled to keep up with surging demand in the wake of the global pandemic — in Q1 this year, the Association for Advancing Automation reported a 19.6% increase in orders across North America alone. While such robots have historically been concentrated in the automobile industry, they have segued into many facets of the economy from ecommerce warehouses to medical equipment assembly.

Sales support platform Orum today announced that it closed a $25 million series A funding round led by Craft Ventures, with participation from several existing backers. The funding brings the company’s total raised to $29 million at a $125 million valuation, and cofounder and CEO Jason Dorfman says the round will be put toward general expansion, mostly focused on product, customer service, and international market expansion.Live conversation is arguably the cornerstone of sales development. According to a HubSpot survey, 20% of customers want to talk during the decision stage, once they’ve chosen a product to buy. Companies are often forced to hire teams of salespeople to create the activity required to hit their pipeline goals, but these entry-level roles can be inefficient and ineffective. Conversion rates for cold calls are typically about 2%, compared with 20% for solid leads and 50% for referrals.

Robotic process automation (RPA) leader Automation Anywhere Inc. (AAI) has grown to become the top public cloud RPA platform with 54% market share according to IDC — more than all the other players combined. This seems to indicate that the company’s major cloud engineering push and marketing partnership with Google have paid off.Cloud RPA is the fastest growing sector of the hot RPA market, and AAI’s recent cloud gains indicate the company has an edge against other RPA leaders, including UiPath and Blue Prism. These results also show that the company is poised to stay competitive even as Microsoft begins moving into the cloud RPA market.However, the cloud market is still only a tiny sliver of the overall RPA market, and the other players have the resources to keep pace, IDC’s intelligent process automation lead Maureen Fleming told VentureBeat. RPA grew 37.1% to $1.7 billion in 2020. RPA cloud accounted for 3.3% share of the total market and increased 387.8%.

Effective use of data science can help business leaders improve their decision-making processes. In the high-speed world of motorsport, those decisions have race-changing implications.That’s certainly the case for Sylvain Filippi, managing director and CTO of the Envision Virgin Racing team, one of the leading teams in Formula E — a single-seater motorsport championship that only uses electric cars. His team produces huge amounts of data, but needs to use this information effectively to produce a competitive advantage.To give his team every chance of success, Filippi’s team started working with global professional services firm Genpact two years ago. Envision Virgin Racing uses Genpact’s data science skills to hone performance on race day. Filippi explained to VentureBeat how the relationship works and the advantages it provides to his team.

A year after the 2020 summer of protest against systemic racism and companies outlining their commitment for greater representation, nearly 20% of organizations are not tracking any diversity metrics in their recruitment or hiring practices.The State of Diversity, Equity and Inclusion in the Workplace report, developed by talent cloud company iCIMS and Talent Board, a nonprofit candidate experience benchmark research organization, was issued to better understand how the changing conversation around Diversity, Equity, and Inclusion (DEI) has actually manifested itself within talent acquisition over the past year. Among the findings, the study revealed that technology implementation is the common tactic in deliberate efforts to remove unconscious bias in hiring.

Late last week, OpenAI confirmed it shuttered its robotics division in part due to difficulties in collecting the data necessary to break through technical barriers. After years of research into machines that can learn to perform tasks like solving a Rubik’s Cube, company cofounder Wojciech Zaremba said it makes sense for OpenAI to shift its focus to other domains, where training data is more readily available.Beyond the commercial motivations for eschewing robotics in favor of media synthesis and natural language processing, OpenAI’s decision reflects a growing philosophical debate in AI and robotics research. Some experts believe training systems in simulation will be sufficient to build robots that can complete complex tasks, like assembling electronics. Others emphasize the importance of collecting real-world data, which can provide a stronger baseline.

In 2019, Google released Translatotron, an AI system capable of directly translating a person’s voice into another language. The system could create synthesized translations of voices to keep the sound of the original speaker’s voice intact. But Translatotron could also be used to generate speech in a different voice, making it ripe for potential misuse in, for example, deepfakes.This week, researchers at Google quietly released a paper detailing Translatotron’s successor, Translatotron 2, which solves the original issue with Translatotron by restricting the system to retain the source speaker’s voice. Moreover, Translatotron 2 outperforms the original Translatotron by “a large margin” in terms of translation quality and naturalness, as well as “drastically” cuts down on undesirable artifacts like babbling and long pauses.

Wiliot, a startup creating a low-cost, self-powered chip that attaches to products to sense physical and environment data, has raised $200 million. The company’s latest tranche, a series C, was led by Softbank Vision Fund 2, and brings the company’s total raised to date to $270 million.Wiliot says that the new money will be invested into hiring engineering, sales, and marketing staff; building out and scaling Wiliot’s software-as-a-service platform; and productizing new sensors and capabilities. The company also plans to integrate with a larger set of partners and invest in silicon production capacity to ensure supply during the worldwide shortage.Trillions of products travel billions of miles from factories to customers’ doorsteps, but for the majority, it’s difficult — if not impossible — to track their real-time status or whereabouts. Lacking this information, global supply chains have been in the dark, with products remaining “off the grid” during their manufacturing, shipping, and consumption journeys. A 2018 Statista survey found that the biggest challenge for global supply chain executives was visibility.

Device42, a cloud discovery platform, this month launched a multicloud migration and recommendation engine that the company claims is the first to support all major cloud providers. Using machine learning to drive its suggestions, Device42 says that the service can perform real-time discovery of IT resources to create an inventory, leveraging dependency mapping to show the relationship and impact of resources on business units.Organizations often face risks in business outages and disruptions attempting to migrate to the cloud. According to IDG research, only 25% achieve their initial goals in the end. Additional reporting by Unisys has found that more than one-third of businesses fail to capture “notable benefits” from their cloud computing projects.

One of NASA’s biggest challenges is identifying where data science skills reside within the organization. Not only is data science a new discipline – it’s also a fast-evolving one. Knowledge for each role is constantly shifting due to technological and business demands.That’s where David Meza, acting branch chief of people analytics and senior data scientist at NASA, believes graph technology can help. His team is building a talent mapping database using Neo4j technology to build a knowledge graph to show the relationships between people, skills, and projects.Meza and his team are currently working on the implementation phase of the project. They eventually plan to formalize the end user application and create an interface to help people in NASA search for talent and job opportunities. Meza told VentureBeat more about the project.

If your company has yet to embrace AI, you’re in a race against the clock. And by my calculations, you have just three years left.How did I arrive at 2024 as the deadline for AI adoption? My prediction — formulated with KUNGFU.AI advisor Paco Nathan — is rooted in us noticing that many futurists’ J curves show innovations typically have a 12-to-15-year window of opportunity, a period between when a technology emerges and when it reaches the point of widespread adoption.While AI can be traced to the mid-1950s and machine learning dates back to the late 1970s, the concept of deep learning was popularized by the “AlexNet” paper published in 2012. Of course, it’s not just machine learning that started the clock ticking.

Recently, voice technology has surged in adoption among enterprises, with 68% of companies reporting they have a voice technology strategy in place, an 18% increase from 2019. And among the companies that don’t, 60% plan to in the next 5 years.The pandemic forever altered enterprises’ tech stack. Many companies already had countless pieces of software in place – from web conferencing to collaboration tools – that made the transition from face-to-face to remote a bit more seamless, but the pandemic spurred the rapid growth of other technologies in both importance and popularity throughout 2020. Voice technology, specifically, experienced a marked increase in adoption among enterprises, with 68% of respondents reporting their company has a voice technology strategy – up 18% from 2019.

Construction digital twins pioneer Cupix today announced an integration with Autodesk’s BIM 360 construction management platform. This is intended to streamline construction workflows that weave up-to-date information about the construction process into Autodesk planning tools.Cupix’s move builds on a prior integration into the Autodesk PlanGrid platform for construction planning. For the vendor and its customers alike, such integrations into the Autodesk environment are a key to bringing digital twins to wider markets. As a mainstay provider of tools for organizing architectural, engineering, and construction management processes, Autodesk will likely influence uptake of digital twins in these key sectors.

British artificial intelligence giant DeepMind has released a database of nearly all human protein structures that it amassed as part of its AlphaFold program. Last year, the organisers of the biennial Critical Assessment of protein Structure Prediction (CASP) recognised AlphaFold as a solution to the grand challenge of figuring out what shapes proteins fold into.... Read more » The post DeepMind releases AlphaFold database of nearly all human protein structures appeared first on AI News.

Blaize, a company developing AI edge computing platforms for automotive, enterprise, and computer vision markets, today announced that it raised $71 million in series D funding led by Franklin Templeton and Temasek, with participation from Denso and other new and existing backers. The company says that the funds will be used to support its go-to-market and R&D efforts.The pandemic has accelerated the adoption of edge computing, or computation and data storage that’s located close to where it’s needed. According to the Linux Foundation’s State of the Edge report, digital health care, manufacturing, and retail businesses are particularly likely to expand their use of edge computing by 2028. This is largely because of the technology’s ability to improve response times and save bandwidth while enabling less constrained data analysis.

An easy to follow tutorial on vector valued functions, parametric equations, space curves, and differentiating vector functions.

Enterprises are increasingly relying on unstructured data for regulatory, analytic, and decision-making purposes. Unstructured data will power analytics, machine learning, and business intelligence.According to the latest figures from research firm ITC, the volume of unstructured data is set to grow from 33 zettabytes in 2018 to 175 zettabytes, or 175 billion terabytes, by 2025. There has to be some kind of data management so organizations have the right kind of data available at the right time. Krishna Subramanian, president and COO of Komprise, a data management software provider, sat down with VentureBeat to discuss the business benefits and challenges associated with unstructured data.Venturebeat: Does the average enterprise IT organization know how much unstructured data they have and how fast it is growing?

Women in the AI field are making research breakthroughs, spearheading vital ethical discussions, and inspiring the next generation of AI professionals. We created the VentureBeat Women in AI Awards to emphasize the importance of their voices, work, and experience, and to shine a light on some of these leaders. In this series, publishing Fridays, we’re diving deeper into conversations with this year’s winners, who we honored recently at Transform 2021. Briana Brownell, winner of VentureBeat’s Women in AI entrepreneur award, didn’t set out in this field to earn accolades. She set out to create an AI that would do her job for her — or at least that’s the joke she likes to tell.Really, she set out to build a company that would combine her data analytics background with AI. In 2015, she launched Pure Strategy, which uses ANIE (an Automated Neural Intelligence Engine) to help companies understand unstructured data. She and her team invented algorithms from scratch to make it happen, and the system has been used by doctors to communicate with patients and with each other across cultural knowledge, for example. She also moonlights as a science communicator, inspiring not just young children — especially girls — but everyone around her.

This article is part of an AI Research Insight Series paid for by Juniper Networks.“Experience is the new uptime,” says Jeff Aaron, VP of enterprise marketing at Juniper Networks. “It’s not enough to look at your dashboard and say, ‘My network is running all green.’ That doesn’t mean your users are having a good experience.”The old network-centric way of operating networks simply can’t keep pace with the soaring number of applications, users and devices within an organization. So it’s no surprise that AI is now powering experience-first networking for both users and operators – and in the process, reducing costs, improving efficiencies and boosting end-user satisfaction.

DataRobot, a startup creating an enterprise AI development platform, today closed a $300 million series G funding round led by Altimeter Capital and Tiger Global, with participation from Morgan Stanley’s Counterpoint Global, Franklin Templeton, ServiceNow Ventures, and Sutter Hill Ventures. The round brings DataRobot’s valuation to $6.3 billion post-money, up from $2.7 billion in November 2020, and comes as the company finalizes the acquisition of Seattle, Washington-based MLOps startup Algorithmia.CEO Dan Wright says that the new funds will be used to “fuel platform innovation” and “enable DataRobot to bring … augmented intelligence” to clients around the world. Specifically, DataRobot plans to build out its go-to-market teams, with Sutter Hill supporting the company’s hiring initiatives.

Google appears to be testing a new feature that allows users to add themselves and parties to the waitlists of restaurants that would normally require a phone call. Powered by Duplex, Google’s AI-driven natural language processing technology that can converse with business owners over the phone, the waitlist capability could benefit hospitality organizations facing surges in traffic as pandemic fears abate.People in the U.S. are returning to restaurants as the coronavirus wanes, leading to overcrowded dining rooms. Complicating matters, even before the pandemic, restaurants struggled to juggle phone-based waitlists, not uncommonly leading to inaccurate wait times and long lines. One survey found that 72% of diners make reservations over the phone, eschewing online, in-person, or mobile app options.

Under new management, Intel aims to recapture a crown that it owned for decades and regain technology leadership in manufacturing chips by 2025.This will be challenging, as the company has to invest tens of billions of dollars and get its technology right in the wake of numerous missteps, but new CEO Pat Gelsinger said at an event that the big chipmaker is accelerating its investments in manufacturing processes and packaging innovations.Intel’s news was one of the most detailed process and packaging technology roadmaps the company has ever provided for its chip factories, and it showcased innovations that will power products through 2025 and beyond.In addition to announcing RibbonFET, its first new transistor architecture in more than a decade, and PowerVia, an industry-first new backside power delivery method, the company highlighted its planned swift adoption of next-generation extreme ultraviolet lithography (EUV), referred to as High Numerical Aperture (High NA) EUV.