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AI Is Harder Than We Think: 4 Key Fallacies in AI Research


Artificial intelligence has been all over headlines for nearly a decade, as systems have made quick progress in long-standing AI challenges like image recognition, natural language processing, and games. Tech companies have sown machine learning algorithms into search and recommendation engines and facial recognition systems, and OpenAI's GPT-3 and DeepMind's AlphaFold promise even more practical applications, from writing to coding to scientific discoveries. Indeed, we're in the midst of an AI spring, with investment in the technology burgeoning and an overriding sentiment of optimism and possibility towards what it can accomplish and when. This time may feel different than previous AI springs due to the aforementioned practical applications and the proliferation of narrow AI into technologies many of us use every day--like our smartphones, TVs, cars, and vacuum cleaners, to name just a few. But it's also possible that we're riding a wave of short-term progress in AI that will soon become part of the ebb and flow in advancement, funding, and sentiment that has characterized the field since its founding in 1956. AI has fallen short of many predictions made over the last few decades; 2020, for example, was heralded by many as the year self-driving cars would start filling up roads, seamlessly ferrying passengers around as they sat back and enjoyed the ride.

How a hybrid workforce can save up to 20 hours a month - Cloud computing news


How productive would your company employees be if they could save two hours a day on regular tasks? With the growth and evolution of today's digital economy, companies face the challenge of managing increasingly complex business processes that involve massive amounts of data. This has also led to repetitive work, like requiring employees to manually perform data-intensive tasks when there are technologies available that could help free their time and automate tasks. According to a WorkMarket report, 53 percent of employees believe they could save up to two hours a day by automating tasks; that equates to roughly 20 hours a month. Working on tasks that could easily be automated is probably not the best use of employees' time, especially if your business is trying to improve productivity or customer service.

The robots are already among us


Andrea Thomaz founded Diligent Robotics in 2016, using what she learned building earlier robot Poli to create a robot aide for nurses called Moxi, so they can focus on patient care rather than restocking supplies, delivering medications or samples, and shuffling around equipment. AI gives Moxi autonomy to navigate hospital halls, while a dexterous arm can recognise and grab objects – all with a smile on its LED face, as this socially-aware robot has facial expressions to set patients at ease.

Agencies struggle to find the right AI solutions -- GCN


Three-quarters of government decision-makers struggle to select the right artificial intelligence solutions for their projects, a new report found. Still, 61% of respondents to a KPGM survey said AI is moderately to fully functional in their organization, according to "Thriving in an AI World," a report the professional services firm released March 9. And in the next two years, respondents said they plan to use AI to improve process automation (48%) and analytics (40%). To determine the best AI solutions, agencies must first define their use case, said Rob Dwyer, KPMG advisory principal specializing in technology in government. Robotic process automation is a common entry point to AI in the public sector because vendors in that area are well established, and it's relatively easy to earn small wins that can drive support for other AI efforts, he said.

Autonomous Driving, AI System on a Chip, Drug Discovery Firms Among Top Funded - AI Trends


The top-funded companies on the recently-released list of top 100 most-promising AI companies to watch from CBInsights, a market intelligence company based in New York, include companies offering autonomous driving software, an AI System on a chip, endpoint security with AI, and a drug discovery company. The list, selected from a base of 6,000 companies, is based on business relations, investor profile, news sentiment analysis, R&D activity, a proprietary scoring system, market potential, competitive landscape, team strength and tech novelty, according to an account in TechRepublic. "This year's cohort spans 18 industries, and is working on everything from climate risk to accelerating drug R&D," stated CB Insights CEO Anand Sanwal. Companies on last year's list went on to raise $5.2 billion in additional financing, including 16 of over $100 million each. Some companies exited via merger or acquisition, IPOs or SPACS.

Tesla admits to California DMV that Elon Musk has been exaggerating about 'full self-driving' cars

Daily Mail - Science & tech

Tesla privately admitted to a California regulator that CEO Elon Musk has been exaggerating plans to have fully-autonomous self-driving cars on the road by 2022. The acknowledgment was revealed in a summary of answers to questions put to the company by with the state's Department of Motor Vehicles. They were released by legal transparency group PlainSite, and first reported by The Verge. During an earnings call in January, Musk told investors he was'highly confident the car will be able to drive itself with reliability in excess of human this year,' reported The Verge. That call came five months after Musk told an AI conference in Shanghai that he was'confident' of producing a fully self-driving car by the end of 2020.

General Motors is Using Artificial Intelligence to Build its Future Vehicles


In the field of technology, artificial intelligence (AI) and self-driving cars are often discussed together. Though AI is being applied at a breakneck pace in a number of industries, the way it's being used in the automotive industry is currently a contentious subject. Every car maker and its parent company is striving to develop artificial intelligence and self-driving technology, and several tech companies and startups are pursuing the same goal. While many people believe that personal, autonomous vehicles are the way of the future, AI and machine learning are being used in a variety of ways in the design and operation of vehicles. General Motors, one of the largest global automaker, is taking a giant step forward towards automotive design by imagining a future of lighter, more powerful, and customizable vehicles.

Building racial and social equity into mobility: What can Ford do about it?


Over the past century, automakers helped transform US cities -- in good ways and bad. The industry helped people move freely, and it delivered good-paying jobs. At the same time, it profited off a network of highways that cut through cities, breaking apart communities of color. Now that the auto industry is at a turning point -- embracing transformative new products, services and business models -- there's an opportunity to root out the inequities built into existing transportation networks. With that opportunity, Ford also sees a chance to build up its reputation as a responsible corporate citizen.

Portable drone hangar gets military certification


A provider of drone-in-a-box systems for applications like inspection and monitoring received a new certification that will make it easier to provide solutions to the defense sector. Easy Aerial recently announced its Easy Guard ground station--essentially a portable hangar for a drone--has received its certification of Military Standard Specification MIL-STD 810G, a standard and broadly recognized defense-industry certification that designates technology as field-ready military equipment. This is significant because it underlines the growing crossover between UAV solutions developed for commercial applications like inspection and pursuits like surveillance and situational awareness that are used by police and military customers. A number of providers now move fluidly between commercial industries and public security & defense, making some privacy advocates uncomfortable. But for a sector that's growing but still trying to catch its footing as the regulatory environment evolves, UAV developers are keen to take advantage of the broad applicability of rugged and task-agnostic hardware, and defense and security, which are embracing drones, represent a market with deep pockets.

IBM's new chip breakthrough may 'quadruple' phone battery life, company claims

The Independent - Tech

IBM has revealed the world's first 2 nanometer (nm) chip technology which can fit up to 50 billion transistors in an area the size of a fingernail, an advance the company claims can lead to "quadrupling cell phone battery life." According to the computing giant, the new breakthrough chip, revealed as a proof-of-concept on Thursday, can improve performance by 45 per cent over current 7nm semiconductors that are used in commercially available products. The company believes this will help meet the demands for increased chip performance and energy efficiency in the era of AI, and the Internet of Things. While initially, the computer chip industry used nanometres – hundreds of times thinner than a single human hair – to measure the physical size of transistors, the nm number has also found its use widely to describe new generations of the technology. Built on IBM's nanosheet technology, the current advance reportedly allows the company to fit up to 50 billion transistors on a chip the size of a fingernail, giving processor builders more space and options to infuse components for workloads like AI and cloud computing.