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Reinforcement learning competition pushes the boundaries of embodied AI

#artificialintelligence

This highlights the complexity of human vision and agency. The next time you go to a supermarket, consider how easily you can find your way through aisles, tell the difference between different products, reach for and pick up different items, place them in your basket or cart, and choose your path in an efficient way. And you're doing all this without access to segmentation and depth maps and by reading items from a crumpled handwritten note in your pocket. Above: Experiments show hybrid AI models that combine reinforcement learning with symbolic planners are better suited to solving the ThreeDWorld Transport Challenge. The TDW-Transport Challenge is in the process of accepting submissions.


University of Waikato installs the world's most advanced AI System

#artificialintelligence

New Zealand's most powerful supercomputer for artificial intelligence applications has been installed at the University of Waikato as part of its commitment positioning New Zealand as a world leader in AI research and development. The NVIDIA DGX A100 is the first computer of its kind in New Zealand and is the world's most advanced system for powering universal AI workloads. The machine has been referred to as the Ferrari of computing because of how fast it can rapidly and efficiently process massive amounts of data, allowing students and researchers at the University to process at lightning-fast speeds, enabling machine learning and artificial intelligence that can solve problems from addressing climate change to managing our biodiversity. Machine learning uses algorithms to explore huge data sets and create models that provide answers or outcomes mirroring human decision making. Models can be trained to recognise things like patterns, facial expressions, and spoken words - or they can find anomalies like credit card fraud.


Gartner says low-code, RPA, and AI driving growth in 'hyperautomation'

#artificialintelligence

Research firm Gartner estimates the market for hyperautomation-enabling technologies will reach $596 billion in 2022, up nearly 24% from the $481.6 billion in 2020. Gartner is expecting significant growth for technology that enables organizations to rapidly identify, vet, and automate as many processes as possible and says it will become a "condition of survival" for enterprises. Hyperautomation-enabling technologies include robotic process automation (RPA), low-code application platforms (LCAP), AI, and virtual assistants. As organizations look for ways to automate the digitization and structuring of data and content, technologies that automate content ingestion, such as signature verification tools, optical character recognition, document ingestion, conversational AI, and natural language technology (NLT), will be in high demand. For example, these tools could be used to automate the process of digitizing and sorting paper records.


New York Returns Its Police 'Robodog' After a Public Outcry

WIRED

The New York Police Department said Thursday it will stop using the "Digidog," a four-legged robot occasionally deployed for recon in dangerous situations. NYPD officials confirmed in a statement it had terminated its contract and will return the dog to vendor Boston Dynamics. Last December, the agency leased the Digidog, nicknamed Spot, for $94,000. John Miller, the police department's deputy commissioner for intelligence and counterterrorism, told The New York Times that the contract was "a casualty of politics, bad information, and cheap sound bites." Miller bemoaned the role of bad press in the backlash, but in many ways the NYPD's own actions were a blueprint for how not to introduce new tech.


Google-led paper pushes back against claims of AI inefficiency

#artificialintelligence

Google this week pushed back against claims by earlier research that large AI models can contribute significantly to carbon emissions. In a paper coauthored by Google AI chief scientist Jeff Dean, researchers at the company say that the choice of model, datacenter, and processor can reduce carbon footprint by up to 100 times and that "misunderstandings" about the model lifecycle contributed to "miscalculations" in impact estimates. Carbon dioxide, methane, and nitrous oxide levels are at the highest they've been in the last 800,000 years. Together with other drivers, greenhouse gases likely catalyzed the global warming that's been observed since the mid-20th century. It's widely believed that machine learning models, too, have contributed to the adverse environmental trend.


Huawei trained the Chinese-language equivalent of GPT-3

#artificialintelligence

For the better part of a year, OpenAI's GPT-3 has remained among the largest AI language models ever created, if not the largest of its kind. Via an API, people have used it to automatically write emails and articles, summarize text, compose poetry and recipes, create website layouts, and generate code for deep learning in Python. But GPT-3 has key limitations, chief among them that it's only available in English. The 45-terabyte dataset the model was trained on drew exclusively from English-language sources. This week, a research team at Chinese company Huawei quietly detailed what might be the Chinese-language equivalent of GPT-3.


Killer farm robot dispatches weeds with electric bolts

The Guardian

In a sunny field in Hampshire, a killer robot is on the prowl. Once its artificial intelligence engine has locked on to its target, a black electrode descends and delivers an 8,000-volt blast. A crackle, a puff of smoke, and the target is dead – a weed, boiled alive from the inside. It is part of a fourth agricultural revolution, its makers say, bringing automation and big data into farming to produce more while harming the environment less. Pressure to cut pesticide use and increasing resistance to the chemicals meant killing weeds was the top priority for the farmers advising the robot company.


Artificial intelligence will maximise efficiency of 5G network operations

#artificialintelligence

Compared with previous types of networks, 5G networks are both more in need of automation and more amenable to automation. Automation tools are still evolving and machine learning is not yet common in carrier-grade networking, but rapid change is expected. Emerging standards from 3GPP, ETSI, ITU and the open source software community anticipate increased use of automation, artificial intelligence (AI) and machine learning (ML). And key suppliers' activities add credibility to the vision and promise of artificially intelligent network operations. "Growing complexity and the need to solve repetitive tasks in 5G and future radio systems necessitate new automation solutions that take advantage of state-of-the-art artificial intelligence and machine learning techniques that boost system efficiency," wrote Ericsson's chief technology officer (CTO), Erik Ekudden, recently.


Self-driving cars to be allowed on UK roads this year

BBC News

"Technologies such as Automated Lane Keeping Systems will pave the way for higher levels of automation in future – and these advances will unleash Britain's potential to be a world leader in the development and use of these technologies, creating essential jobs while ensuring our roads remain among the safest on the planet."


Are Crossword Solvers About to Go the Way of Chess Players?

Slate

Nearly 1,300 people spent this past weekend racing to fill little boxes inside larger boxes, ever mindful of spelling, trivia, wordplay, and a ticking clock. They were competitors--newcomers, ardent hobbyists, and elite speed solvers--in the American Crossword Puzzle Tournament, the pastime's most prestigious competition. And most of them got creamed by some software. The annual event, normally set in a packed hotel ballroom with solvers separated by yellow dividers, was virtual this year, pencils swapped for keyboards. After millions of little boxes had been filled, a computer program topped the leaderboard for the first time.