Artificial intelligence is enabling many scientific breakthroughs, especially in fields of study that generate high volumes of complex data such as neuroscience. As impossible as it may seem, neuroscientists are making strides in decoding neural activity into speech using artificial neural networks. Yesterday, the neuroscience team of Gopala K. Anumanchipalli, Josh Chartier, and Edward F. Chang of University of California San Francisco (UCSF) published in Nature their study using artificial intelligence and a state-of-the-art brain-machine interface to produce synthetic speech from brain recordings. The concept is relatively straightforward--record the brain activity and audio of participants while they are reading aloud in order to create a system that decodes brain signals for vocal tract movements, then synthesize speech from the decoded movements. The execution of the concept required sophisticated finessing of cutting-edge AI techniques and tools.

When people think of Artificial Intelligence (AI), the major image that pops up in their heads is that of a robot gliding around and giving mechanical replies. There are many forms of AI but humanoid robots are one of the most popular forms. They have been depicted in several Hollywood movies and if you are a fan of science fiction, you might have come across a few humanoids. One of the earliest forms of humanoids was created in 1495 by Leonardo Da Vinci. It was an armor suit and it could perform a lot of human functions such as sitting, standing and walking.

AI in commerce is a fast-growing -- and highly lucrative -- industry. A recent report published by Juniper Research predicts that global retail spending on AI and machine learning will reach $7.3 billion per year by 2022, up from an estimated $2 billion in 2018. Stores with and without brick-and-mortar presences cite cost savings, increased productivity, and more informed business decision-making as the leading adoption drivers; that's part of the reason why retail AI deployments experienced a sevenfold increase from 2016, according to Capgemini. Vue.ai is looking to cash in on the trend, and it's raising venture capital to lay the stage for its next round of growth. The Fremont, California-based subbrand of AI startup Mad Street Den today announced that it's raised $17 million in a series B financing round led by Falcon Edge Capital, with participation from Sequoia Capital India and KDDI Innovation Fund's Global Brain.

Neural networks are changing the way that Lex Flagel studies DNA. Lex's recent paper – The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference – demonstrates how simple deep learning techniques can be used to tackle the ever-changing field of DNA research. Lex is the Quantitative Genetics Team Lead at Bayer Crop Science. At Bayer, Lex focuses on genetics, genomics, bioinformatics, and data science on crops like corn and soybeans. Don't worry -- we'll dig into what all those terms mean! Lex has a PhD in Genetics from Iowa State University. I'm excited to share my conversation with Lex for this Humans of Machine Learning (#humansofml) interview. In this post, we're going to learn about how Lex uses deep learning to study population genetics, as well as Lex's own journey with data science and AI.

In 2013, IBM sold the University of Texas' MD Anderson Cancer Center on an audacious idea: that a single AI-powered platform, IBM Watson, could lend a digital hand to battle one of mankind's most abominable diseases--cancer. In less than four years, the trailblazing moonshot fell apart. Yet even as Watson stumbled, it provided valuable insight--and a powerful peek ahead--at how machine learning technologies could one day supplement and revolutionize almost everything doctors do. The question isn't if AI is coming to medicine. At its best, machine learning can tap into the collective experience of nearly all clinicians, providing a single doctor with the experience of millions of similar cases to make informed decisions.

As agencies continue to adopt artificial intelligence and machine learning, they're working to keep their employees up to speed in new technologies and cybersecurity defenses. Lynne Parker, assistant director for AI at the White House Office of Science and Technology Policy (OSTP), acknowledged at an April 18 event hosted by the National Academy for Public Administration that AI presents "a lot of workforce challenges." Parker said that while government doesn't "at the moment" have a holistic approach toward training and preparing the workforce for technological advancements, "agencies are stepping up on their own to create opportunities for people to enroll" in IT, cyber and AI training. "Agencies are taking an active role in trying to help people learn those kinds of opportunities," she said. Because agencies understand "the kinds of skills and the kinds of work that they do, they're best suited to create these kinds of training programs," she added, citing the General Services Administration as an example of an agency that's promoting new skills.

In the era of Trumpian politics the public forum is no longer the evening news or the morning paper: it's Twitter. We decided to see which politicians were embracing the platform to discuss what we feel will be one of the most important issues of their potential presidency: artificial intelligence. What we found wasn't good. We gathered a list of every AI-related tweet 2020 Democratic hopefuls sent over the past 12 months. Our expectation was that there'd be a few thousand or so, and we'd spend the better part of the week parsing the information for insights.

In China, blockchain technology is increasingly employed to settle court cases, local news outlet Global Times reported on April 25. Speaking at the 2019 Forum on China Intellectual Property Protection, Zhang Wen, president of the Beijing Internet Court -- which was established in September 2018, and has since processed 14,904 cases -- reportedly said that the court employs technologies such as artificial intelligence (AI) and blockchain to render judgement. Zhang reportedly told the Global Times that "of the 41 cases concluded [with blockchain technology] so far, parties chose to settle out of court rather than litigate in 40 cases with compelling evidence from blockchain. He also noted that the court had deployed blockchain in 58 cases to collect and provide evidence. "In the current use of AI as an assistant to make rulings, efficiency is prioritized over accuracy.

Walmart this morning unveiled a new "store of the future" and test grounds for emerging technologies, including AI-enabled cameras and interactive displays. The store, a working concept called the Intelligent Retail Lab -- or "IRL" for short -- operates out of a Walmart Neighborhood Market in Levittown, N.Y. The store is open to customers and is one of Walmart's busiest Neighborhood Market stores, containing more than 30,000 items, the retailer says, which allows it to test out technology in a real-world environment. Similar to Amazon Go's convenience stores, the store has a suite of cameras mounted in the ceiling. But unlike Amazon Go, which is a grab-and-go store with smaller square footage, Walmart's IRL spans 50,000 square feet of retail space and is staffed by more than 100 employees.

Charlie Friend, the critics, the album and the Beatles reunion (two years after Lennon was actually assassinated) are all figments of Ian McEwan's fertile imagination in his latest novel, "Machines Like Me." The Beatles' presence is a tiny diversion in a counterfactual novel by the author of books including "The Innocent," "Amsterdam," and "Atonement." Set in a world where the atom bomb was never dropped and John Kennedy survived his Dallas shooting, the crucial alternative reality is that Alan Turing, the genius who broke Nazi Germany's secret codes during World War II, was not hounded into suicide for being homosexual -- instead, he lived to spark huge technological breakthroughs that led to an earlier Digital Age, with progress sped up by Turing's generous open sourcing.