Artificial intelligence is to be used to tackle the most deadly parasitic diseases in the developing world, tech company DeepMind has announced. The BBC reports: The London-based Alphabet-owned lab will work with the Drugs for Neglected Diseases initiative (DNDI) to treat Chagas disease and Leishmaniasis. Scientists spend years in laboratories mapping protein structures. But last year, DeepMind's AlphaFold program was able to achieve the same accuracy in a matter of days. Many diseases are linked to the roles of proteins in: catalysing chemical reactions (enzymes); fighting disease (antibodies); and acting as chemical messengers (hormones such as insulin). And knowing the 3D structure of a protein is important in developing treatments for, among others, cancer, dementia and infectious diseases. Prof Dame Janet Thornton, of the European Bioinformatics Institute, told BBC News: "Most new drugs in recent years have been developed using protein-structural data as one part of the process. "There are, however, many other aspects which need to be taken into account, which, due to lack of data, may not be amenable to AI approaches." But the predictions would be "particularly valuable" for pathogens with unknown protein structures, including some neglected diseases. "Developing new AI approaches for designing such drugs is a new challenge but one to which the new AI techniques can be applied and this holds out great hope for the future," Dame Janet added.

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This may sound like something straight out of a sci-fi movie, but Canon has rolled out new AI cameras that use "smile recognition" technology to ensure that only happy employees are allowed into its offices. From a report: Back in 2020, the China-based Canon subsidiary Canon Information Technology introduced an "intelligent IT solution" for corporate offices that includes 5 different functional modules, one of which is "smiley face access control. In addition, based on the corporate culture of 'moving and always being,' Canon has always advocated the concepts of 'laughing' and 'big health,' and hopes to bring happiness and health to everyone in the post-epidemic era," Canon wrote in a press release. "Therefore, in the [...] intelligent IT solution, a new experience of smile recognition is specially incorporated. It is hoped that smiles can let everyone relax and get healthy, so as to create a more pleasant working atmosphere and improve efficiency."

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Check out this video footage of the sleek Mayflower 400 slicing through the water, hoping to retrace the historic 1620 journey of the famous ship which carried pilgrims to America. Unfortunately, unlike the real Mayflower, this robotic 21st-century doppelganger "had to turn back Friday to fix a mechanical problem," reports the Associated Press: Nonprofit marine research organization ProMare, which worked with IBM to build the autonomous ship, said it made the decision to return to base "to investigate and fix a minor mechanical issue" but hopes to be back on the trans-Atlantic journey as soon as possible. With no humans on board the ship, there's no one to make repairs while it's at sea. Piloted by artificial intelligence technology, the 50-foot (15-meter) Mayflower Autonomous Ship began its trip early Tuesday, departing from Plymouth, England, and spending some time off the Isles of Scilly before it headed for deeper waters. It was supposed to take up to three weeks to reach Provincetown on Cape Cod before making its way to Plymouth, Massachusetts. If successful, it would be the largest autonomous vessel to cross the Atlantic.

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An anonymous reader shares a report: Google CEO Sundar Pichai last month previewed an artificial intelligence model that he said would enable people to have open-ended conversations with technology. But current and former employees who have worked with the language model say enabling coherent, free-flowing and accurate dialogue between humans and technology remains a tall order. As a result, Google is taking a more incremental step in conversational AI by preparing to teach foreign languages through Google Search [Editor's note: the link may be paywalled; alternative source], according to people involved in the work. The project, referred to internally as Tivoli, grew out of its Google Research unit and is likely to be rolled out later this year. It will initially work over text, and the exact look and feel of the instruction couldn't be learned. Googlers are also discussing ways to eventually add the functionality to its voice assistant and YouTube product lines. In YouTube, for example, it could generate language quizzes where viewers record themselves after watching a video and the AI provides an assessment of how they performed. A Google spokesperson did not have a comment. Teaching foreign languages allows Google to move more fluid, conversational AI beyond silly exchanges to a practical-use but low-stakes case, the people said. Using the wrong tense or phrase would be unlikely to cause serious harm to users. AI researchers have for decades worked to foster dialogue between computers and humans that feels real, picks up the nuance of how people communicate and simplifies tasks. Such aspirational technology has been featured in movies like "Her" in which a man communicates with -- and falls in love with -- a virtual assistant.

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McDonald's equiped 10 of its restaurants in Chicago with automated speech-recognition for their drive-through windows. Now they're facing a potential class-action lawsuit. Long-time Slashdot reader KindMind shares this report from the Register: McDonald's has been accused of illegally collecting and processing customers' voice recordings without their consent in the U.S. state of Illinois... The state has some of the strictest data privacy laws; its Biometric Information Privacy Act (BIPA) states: "No private entity may collect, capture, purchase, receive through trade, or otherwise obtain a person's or a customer's biometric identifier or biometric information." unless it receives written consent. Shannon Carpenter, a resident of Illinois, sued [PDF] McDonald's in April on behalf of himself and all other affected state residents. He claimed the fast-chow biz has broken BIPA by not obtaining written consent from its customers to collect and process their voice data, nor has it explained in its privacy policy how or if the data is stored or deleted. His lawsuit also stated that McDonald's has been experimenting with AI software taking orders at its drive thrus since last year. "Plaintiff, like the other class members, to this day does not know the whereabouts of his voiceprint biometrics which defendant obtained," Carpenter's lawsuit stated. Under the BIPA, people can receive up to $5,000 in damages from private entities for each violation committed "intentionally or recklessly," or $1,000 if each violation was from negligence instead. The suit also claimed the machine-learning software built by McD Tech Labs doesn't just transcribe speech into text, it processes audio samples to glean all sorts of personal information to predict a customer's "age, gender, accent, nationality, and national origin."

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An anonymous reader quotes a report from The Wall Street Journal: The Biden administration launched an initiative Thursday aiming to make more government data available to artificial intelligence researchers, part of a broader push to keep the U.S. on the cutting edge of the crucial new technology. The National Artificial Intelligence Research Resource Task Force, a group of 12 members from academia, government, and industry led by officials from the White House Office of Science and Technology Policy and the National Science Foundation, will draft a strategy for potentially giving researchers access to stores of data about Americans, from demographics to health and driving habits. They would also look to make available computing power to analyze the data, with the goal of allowing access to researchers across the country. The task force, which Congress mandated in the National Artificial Intelligence Initiative Act of 2020, is part of an effort across the government to ensure the U.S. remains at the vanguard of technological advancements. Many researchers, particularly in academia, simply don't have access to these computational resources and data, and this is hampering innovation. One example: The Transportation Department has access to a set of data gathered from vehicle sensors about how people drive, said Erwin Gianchandani, senior adviser at the National Science Foundation and co-chairman of the new AI task force. "Because you have very sensitive data about individuals, there are challenges in being able to make that data available to the broader research community," he said. On the other hand, if researchers could get access, they could develop innovations designed to make driving safer. Census data, medical records, and other data sets could also potentially be made available for research by both private companies and academic institutions, officials said. They said the task force will evaluate how to make such data available while protecting Americans' privacy and addressing other ethical concerns.

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An anonymous reader shares an excerpt from an interview The Guardian conducted with Microsoft's Kate Crawford. "Kate Crawford studies the social and political implications of artificial intelligence," writes Zoe Corbyn via The Guardian. "She is a research professor of communication and science and technology studies at the University of Southern California and a senior principal researcher at Microsoft Research. Her new book, Atlas of AI, looks at what it takes to make AI and what's at stake as it reshapes our world." Here's an excerpt from the interview: What should people know about how AI products are made? We aren't used to thinking about these systems in terms of the environmental costs. But saying, "Hey, Alexa, order me some toilet rolls," invokes into being this chain of extraction, which goes all around the planet... We've got a long way to go before this is green technology. Also, systems might seem automated but when we pull away the curtain we see large amounts of low paid labour, everything from crowd work categorizing data to the never-ending toil of shuffling Amazon boxes. AI is neither artificial nor intelligent. It is made from natural resources and it is people who are performing the tasks to make the systems appear autonomous. Problems of bias have been well documented in AI technology. Can more data solve that? Bias is too narrow a term for the sorts of problems we're talking about. Time and again, we see these systems producing errors -- women offered less credit by credit-worthiness algorithms, black faces mislabelled -- and the response has been: "We just need more data." But I've tried to look at these deeper logics of classification and you start to see forms of discrimination, not just when systems are applied, but in how they are built and trained to see the world. Training datasets used for machine learning software that casually categorize people into just one of two genders; that label people according to their skin color into one of five racial categories, and which attempt, based on how people look, to assign moral or ethical character. The idea that you can make these determinations based on appearance has a dark past and unfortunately the politics of classification has become baked into the substrates of AI. What do you mean when you say we need to focus less on the ethics of AI and more on power? Ethics are necessary, but not sufficient. More helpful are questions such as, who benefits and who is harmed by this AI system? And does it put power in the hands of the already powerful? What we see time and again, from facial recognition to tracking and surveillance in workplaces, is these systems are empowering already powerful institutions -- corporations, militaries and police. What's needed to make things better? Much stronger regulatory regimes and greater rigour and responsibility around how training datasets are constructed. We also need different voices in these debates -- including people who are seeing and living with the downsides of these systems. And we need a renewed politics of refusal that challenges the narrative that just because a technology can be built it should be deployed.

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"For the first time, artificial intelligence was a key component and power multiplier in fighting the enemy," says a senior officer in the intelligence corps of the Israeli military, describing the technology's use in 11 days of fighting in the Gaza Strip. They're quoted in a Jerusalem Post article on "the world's first AI war": Soldiers in Unit 8200, an Intelligence Corps elite unit, pioneered algorithms and code that led to several new programs called "Alchemist," "Gospel" and "Depth of Wisdom," which were developed and used during the fighting. Collecting data using signal intelligence, visual intelligence, human intelligence , geographical intelligence, and more, the Israel Defense Forces (IDF) has mountains of raw data that must be combed through to find the key pieces necessary to carry out a strike. "Gospel" used AI to generate recommendations for troops in the research division of Military Intelligence, which used them to produce quality targets and then passed them on to the IAF to strike... While the IDF had gathered thousands of targets in the densely populated coastal enclave over the past two years, hundreds were gathered in real time, including missile launchers that were aimed at Tel Aviv and Jerusalem. The military believes using AI helped shorten the length of the fighting, having been effective and quick in gathering targets using super-cognition. The IDF carried out hundreds of strikes against Hamas and PIJ, including rocket launchers, rocket manufacturing, production and storage sites, military intelligence offices, drones, commanders' residences and Hamas's naval commando unit. Israel has destroyed most of the naval commando unit's infrastructure and weaponry, including several autonomous GPS-guided submarines that can carry 30 kg. of explosives. IDF Unit 9900's satellites have gathered geographical intelligence over the years. They were able to automatically detect changes in terrain in real time so that during the operation, the military was able to detect launching positions and hit them after firing. For example, Unit 9900 troops using satellite imagery were able to detect 14 rocket launchers that were located next to a school... One strike, against senior Hamas operative Bassem Issa, was carried out with no civilian casualties despite being in a tunnel under a high-rise building surrounded by six schools and a medical clinic... Hamas's underground "Metro" tunnel network was also heavily damaged over the course of several nights of airstrikes. Military sources said they were able to map the network, consisting of hundreds of kilometers under residential areas, to a degree where they knew almost everything about them. The mapping of Hamas's underground network was done by a massive intelligence-gathering process that was helped by the technological developments and use of Big Data to fuse all the intelligence.

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A Canadian startup called Listing AI is using AI to quickly churn out computer-generated descriptions of real estate. All users need to do is give it some details about the home, and the AI does the rest. CNN reports: "L O V E L Y Oakland!" the house description began. It went on to give a slew of details about the 1,484 square-foot home -- light-filled, charming, Mediterranean-style, with a yard that "boasts lush front landscaping" -- and finished by describing the "cozy fireplace" and "rustic-chic" pressed tin ceiling in the living room. The results still need work: The real-life Oakland, California, home that fits with the above description (which my family is currently selling) actually has a pressed tin ceiling in the dining room, rather than the living room, for instance. The descriptions Listing AI created for me are not nearly as specific or well-written as the one crafted by our (human) realtor. And I had to provide the website with a lot of information about different rooms and features of the house and the outdoor landscaping -- a process that felt a bit like real-estate Mad Libs -- before the website was able to come up with several different descriptions. But the general coherence of the descriptions that Listing AI proposed within seconds of my submission provides yet another sign that AI is getting better at a task that was traditionally seen as uniquely human -- and shows how people may be able to work with the technology, rather than fearing it may replace us. It probably won't do all the work of writing a house description for you, but according to Listing AI co-founder Mustafa Al-Hayali, that's not the point. He hopes it will complete about 80% to 90% of the work for coming up with a home description, which may be completed by a realtor or a copy writer. "I don't believe it's meant to replace a person when it comes to completing a task, but it's supposed to make their job a whole lot easier," Al-Hayali told CNN Business. "It can generate ideas you can use." The information used in the app is processed by GPT-3, an AI model from nonprofit research company OpenAI. According to MIT Technology Review, GPT-3 could herald a new type of search engine.

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Researchers at Intel Labs have applied machine learning techniques to GTA 5 to make it look incredibly realistic. Gizmodo reports: [I]nstead of training a neural network on famous masterpieces, the researchers at Intel Labs relied on the Cityscapes Dataset, a collection of images of a German city's urban center captured by a car's built-in camera, for training. When a different artistic style is applied to footage using machine learning techniques, the results are often temporally unstable, which means that frame by frame there are weird artifacts jumping around, appearing and reappearing, that diminish how real the results look. With this new approach, the rendered effects exhibit none of those telltale artifacts, because in addition to processing the footage rendered by Grand Theft Auto V's game engine, the neural network also uses other rendered data the game's engine has access to, like the depth of objects in a scene, and information about how the lighting is being processed and rendered. That's a gross simplification -- you can read a more in-depth explanation of the research here -- but the results are remarkably photorealistic. The surface of the road is smoothed out, highlights on vehicles look more pronounced, and the surrounding hills in several clips look more lush and alive with vegetation. What's even more impressive is that the researchers think, with the right hardware and further optimization, the gameplay footage could be enhanced by their convolutional network at "interactive rates" -- another way to say in real-time -- when baked into a video game's rendering engine.

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An anonymous reader quotes a report from The Verge: Amazon's Alexa has a voice familiar to millions: calm, warm, and measured. But like most synthetic speech, its tones have a human origin. There was someone whose voice had to be recorded, analyzed, and algorithmically reproduced to create Alexa as we know it now. Amazon has never revealed who this "original Alexa" is, but journalist Brad Stone says he tracked her down, and she is Nina Rolle, a voiceover artist based in Boulder, Colorado. The claim comes from Stone's upcoming book on the tech giant, Amazon Unbound, an excerpt of which is published here in Wired. Neither Amazon nor Rolle confirmed or denied Stone's reporting, which he says is based on conversations with the professional voiceover community, but Rolle's voice alone makes for a compelling case. Here's how Stone writes up the process in selecting Alexa's voice: "Believing that the selection of the right voice for Alexa was critical, [then-Amazon exec Greg] Hart and colleagues spent months reviewing the recordings of various candidates that GM Voices produced for the project, and presented the top picks to Bezos. The Amazon team ranked the best ones, asked for additional samples, and finally made a choice. Bezos signed off on it. Characteristically secretive, Amazon has never revealed the name of the voice artist behind Alexa. I learned her identity after canvasing the professional voice-over community: Boulder, Colorado -- based voice actress and singer Nina Rolle. Her professional website contains links to old radio ads for products such as Mott's Apple Juice and the Volkswagen Passat -- and the warm timbre of Alexa's voice is unmistakable. Rolle said she wasn't allowed to talk to me when I reached her on the phone in February 2021. When I asked Amazon to speak with her, they declined."

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Long-time Slashdot reader AmiMoJo quotes the Verge's warning about "deepfake geography: AI-generated images of cityscapes and countryside." Specifically, geographers are concerned about the spread of fake, AI-generated satellite imagery. Such pictures could mislead in a variety of ways. They could be used to create hoaxes about wildfires or floods, or to discredit stories based on real satellite imagery... Deepfake geography might even be a national security issue, as geopolitical adversaries use fake satellite imagery to mislead foes... The first step to tackling these issues is to make people aware there's a problem in the first place, says Bo Zhao, an assistant professor of geography at the University of Washington. Zhao and his colleagues recently published a paper on the subject of "deep fake geography," which includes their own experiments generating and detecting this imagery... As part of their study, Zhao and his colleagues created software to generate deepfake satellite images, using the same basic AI method (a technique known as generative adversarial networks, or GANs) used in well-known programs like ThisPersonDoesNotExist.com. They then created detection software that was able to spot the fakes based on characteristics like texture, contrast, and color. But as experts have warned for years regarding deepfakes of people, any detection tool needs constant updates to keep up with improvements in deepfake generation.

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The White House has launched a new website, AI.gov, to make artificial intelligence research more accessible across the nation. Axios: The U.S. once led significantly in the global artificial intelligence race, but now risks being overtaken by China. This is one step the White House is taking to drum up excitement for AI and broaden educational opportunities in the field. The website's target audience is the general public, and its purpose is to make public information available on AI more visible to someone like a teacher or student interested in science. Users will be able to visit the website to learn how artificial intelligence is being used across the nation in a variety of ways, including to respond to the COVID pandemic and weather forecasting, for example. It's also meant to be a tool to advance research.

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"Despite early claims by #Tesla #ElonMusk, Autopilot WAS engaged in tragic crash in The Woodlands," tweeted U.S. Congressman Kevin Brady on Wednesday. (Adding "We need answers.") But maybe it depends on how you define Autopilot. CNN reports: Tesla said Monday that one of Autopilot's features was active during the April 17 crash that killed two men in Spring, Texas.... Lars Moravy, Tesla's vice president of vehicle engineering, said on the company's earnings call Monday that Tesla's adaptive cruise control was engaged and accelerated to 30 mph before the car crashed. Autopilot is a suite of driver assistance features, including traffic-aware cruise control and Autosteer, according to Tesla's website... The North American owner's manuals for the Model 3, Model S and Model X, all describe traffic-aware cruise control as an Autopilot feature. Tesla's revelation may be at odds with the initial description of the crash from its CEO Elon Musk, who said two days after the crash that "data logs recovered so far show Autopilot was not enabled." Alternately, Forbes suggests there may just be some confusion, noting that earnings call included descriptions of tests Tesla performed on one of their own cars after the accident. So when they said adaptive cruise control "only accelerated the car to 30mph [over] the distance before the car crashed," they could just have been referring to their own experiments. (Tesla also points out adaptive cruise control only engages when the driver is buckled — and disengages slowly if they're unbuckled — and after the Texas crash all seat belts were unbuckled.) Why so much confusion? Part of the problem may be, as CNN points out, that Tesla "generally does not engage with the professional news media." But The Drive shares another theory about the crash: A relative of the deceased told a local news station that the owner allegedly "may have hopped in the back seat after backing the car out of the driveway." Moments later, the car crashed when it failed to negotiate a turn at high speed. CNN adds: Bryan Reimer, the associate director of the New England University Transportation Center at MIT, who studies driver assistance systems like Autopilot, said one of the plausible explanations for the crash is that the driver was confused and thought they had activated Autosteer, when only traffic-aware cruise control had been turned on. "The general understanding of Autopilot is that it's one feature, but in reality it is two things bolted together," said Reimer, referring to traffic-aware cruise control and Autosteer. But according to the Washington Post, Tesla also disputes that theory: Tesla executives on Monday claimed a driver was behind the wheel at the time of a fatal crash that killed two in suburban Houston this month, contradicting local authorities who have previously said they were certain no one was in that seat. Tesla made the statement on its earnings call Monday... Lars Moravy, the company's vice president of vehicle engineering, said the steering wheel was "deformed," indicating a driver's presence at the time of the crash... Mark Herman, constable for Harris County Precinct 4, told the station KHOU that police were "100 percent certain that no one was in the driver's seat."

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Long-time Slashdot reader gregstumph writes: Dr.Fill, a software program that solves crossword puzzles, finished in first place at the 2021 American Crossword Puzzle Tournament, for the first time ever (its previous best was 11th place in 2017). Dr.Fill, created by Matt Ginsberg, has been participating as a non-competitor at the tournament since 2012. This year, Ginsberg made improvements to Dr.Fill with the assistance of a team from the Berkeley NLP Group. The program finished "a scant 15 points ahead of Erik Agard on the main block of puzzles 1-7," Ginsberg posted on Facebook. This was followed by "then solving the playoff puzzle perfectly in 49 seconds" (while according to Wikipedia the fastest human competitor, Tyler Hinman, took three minutes to solve the puzzle). The Facebook post adds graciously, "Total kudos to Erik, the true winner of puzzles 1-7, and to Tyler Hinman, the winner of the event itself."

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An anonymous reader quotes a report from The New York Times: The European Union unveiled strict regulations on Wednesday to govern the use of artificial intelligence, a first-of-its-kind policy that outlines how companies and governments can use a technology seen as one of the most significant, but ethically fraught, scientific breakthroughs in recent memory. The draft rules would set limits around the use of artificial intelligence in a range of activities, from self-driving cars to hiring decisions, bank lending, school enrollment selections and the scoring of exams. It would also cover the use of artificial intelligence by law enforcement and court systems -- areas considered "high risk" because they could threaten people's safety or fundamental rights. Some uses would be banned altogether, including live facial recognition in public spaces, though there would be several exemptions for national security and other purposes. The108-page policy is an attempt to regulate an emerging technology before it becomes mainstream. The rules have far-reaching implications for major technology companies that have poured resources into developing artificial intelligence, including Amazon, Google, Facebook and Microsoft, but also scores of other companies that use the software to develop medicine, underwrite insurance policies and judge credit worthiness. Governments have used versions of the technology in criminal justice and the allocation of public services like income support. Companies that violate the new regulations, which could take several years to move through the European Union policymaking process, could face fines of up to 6 percent of global sales. The European Union regulations would require companies providing artificial intelligence in high-risk areas to provide regulators with proof of its safety, including risk assessments and documentation explaining how the technology is making decisions. The companies must also guarantee human oversight in how the systems are created and used. Some applications, like chatbots that provide humanlike conversation in customer service situations, and software that creates hard-to-detect manipulated images like "deepfakes," would have to make clear to users that what they were seeing was computer generated. [...] Release of the draft law by the European Commission, the bloc's executive body, drew a mixed reaction. Many industry groups expressed relief that the regulations were not more stringent, while civil society groups said they should have gone further.

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Translation tools from Google and other companies could be contributing to significant misunderstanding of legal terms with conflicting meanings such as "enjoin," according to research due to be presented at an academic workshop on Monday. From a report: Google's translation software turns an English sentence about a court enjoining violence, or banning it, into one in the Indian language of Kannada that implies the court ordered violence, according to the new study. "Enjoin" can refer to either promoting or restraining an action. Mistranslations also arise with other contronyms, or words with contradictory meanings depending on context, including "all over," "eventual" and "garnish," the paper said. Google said machine translation is "is still just a complement to specialized professional translation" and that it is "continually researching improvements, from better handling ambiguous language, to mitigating bias, to making large quality gains for under-resourced languages." The study's findings add to scrutiny of automated translations generated by artificial intelligence software. Researchers previously have found programs that learn translations by studying non-diverse text perpetuate historical gender biases, such as associating "doctor" with "he." The new paper raises concerns about a popular method companies use to broaden the vocabulary of their translation software. They translate foreign text into English and then back into the foreign language, aiming to teach the software to associate similar ways of saying the same phrase.

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Several U.S. banks have started deploying camera software that can analyze customer preferences, monitor workers and spot people sleeping near ATMs, even as they remain wary about possible backlash over increased surveillance, Reuters reported Monday, citing more than a dozen banking and technology sources. From the report: Previously unreported trials at City National Bank of Florida and JPMorgan Chase & Co as well as earlier rollouts at banks such as Wells Fargo & Co offer a rare view into the potential U.S. financial institutions see in facial recognition and related artificial intelligence systems. Widespread deployment of such visual AI tools in the heavily regulated banking sector would be a significant step toward their becoming mainstream in corporate America. Bobby Dominguez, chief information security officer at City National, said smartphones that unlock via a face scan have paved the way. "We're already leveraging facial recognition on mobile," he said. "Why not leverage it in the real world?" City National will begin facial recognition trials early next year to identify customers at teller machines and employees at branches, aiming to replace clunky and less secure authentication measures at its 31 sites, Dominguez said. Eventually, the software could spot people on government watch lists, he said. JPMorgan said it is "conducting a small test of video analytic technology with a handful of branches in Ohio." Wells Fargo said it works to prevent fraud but declined to discuss how.

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"Jensen Huang, the CEO of Nvidia, the nation's most valuable semiconductor company, with a stock price of $645 a share and a market cap of $400 billion, is out to create the metaverse," writes Time magazine. Huang defines it as "a virtual world that is a digital twin of ours." Huang credits author Neal Stephenson's Snow Crash, filled with collectives of shared 3-D spaces and virtually enhanced physical spaces that are extensions of the Internet, for conjuring the metaverse. This is already playing out with the massively popular online games like Fortnite and Minecraft, where users create richly imagined virtual worlds. Now the concept is being put to work by Nvidia and others. Partnering with Nvidia, BMW is using a virtual digital twin of a factory in Regensburg, Germany, to virtually plan new workflows before deploying the changes in real time in their physical factory. The metaverse, says Huang, "is where we will create the future" and transform how the world's biggest industries operate... Not to make any value judgments about the importance of video games, but do you find it ironic that a company that has its roots in entertainment is now providing vitally important computing power for drug discovery, basic research and reinventing manufacturing? No, not at all. It's actually the opposite. We always started as a computing company. It just turned out that our first killer app was video games... How important is the advent and the adaptation of digital twins for manufacturing, business and society at large? In the future, the digital world or the virtual world will be thousands of times bigger than the physical world. There will be a new New York City. There'll be a new Shanghai. Every single factory and every single building will have a digital twin that will simulate and track the physical version of it. Always. By doing so, engineers and software programmers could simulate new software that will ultimately run in the physical version of the car, the physical version of the robot, the physical version of the airport, the physical version of the building. All of the software that's going to be running in these physical things will be simulated in the digital twin first, and then it will be downloaded into the physical version. And as a result, the product keeps getting better at an exponential rate. The second thing is, you're going to be able to go in and out of the two worlds through wormholes. We'll go into the virtual world using virtual reality, and the objects in the virtual world, in the digital world, will come into the physical world, using augmented reality. So what's going to happen is pieces of the digital world will be temporarily, or even semipermanently, augmenting our physical world. It's ultimately about the fusion of the virtual world and the physical world. See also this possibly related story, "Nvidia's newest AI model can transform single images into realistic 3D models."

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Aflorithmic, an AI-driven audio cloning startup, has created a digital version of Albert Einstein using AI voice cloning technology drawing on audio records of the famous scientist's actual voice. TechCrunch reports: Alforithmic says the "digital Einstein" is intended as a showcase for what will soon be possible with conversational social commerce. Which is a fancy way of saying deepfakes that make like historical figures will probably be trying to sell you pizza soon enough, as industry watchers have presciently warned. The startup also says it sees educational potential in bringing famous, long-deceased figures to interactive "life." Or, well, an artificial approximation of it -- the "life" being purely virtual and Digital Einstein's voice not being a pure tech-powered clone either; Alforithmic says it also worked with an actor to do voice modelling for the chatbot (because how else was it going to get Digital Einstein to be able to say words the real-deal would never even have dreamt of saying -- like, er, "blockchain"?). So there's a bit more than AI artifice going on here too. In a blog post discussing how it recreated Einstein's voice the startup writes about progress it made on one challenging element associated with the chatbot version -- saying it was able to shrink the response time between turning around input text from the computational knowledge engine to its API being able to render a voiced response, down from an initial 12 seconds to less than three (which it dubs "near-real-time"). But it's still enough of a lag to ensure the bot can't escape from being a bit tedious. The report notes that the video engine powering the 3D character rendering components of this "digital human" version of Einstein is the work of another synthesized media company, UneeQ, which is hosting the interactive chatbot version on its website.

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