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Category: robotics/AI – Page 1062

Back in 2002, the science fiction film Minority Report once again reignited futuristic imaginations about a world and police state gone too far. At the time, the movie inspired plenty of speculation about the future of our society, how computers would interact with us, and how law enforcement would be carried out proactively based on intent. In the movie, they combined technology with the psychic abilities of the “precogs,” to proactively prevent crimes.

The precogs had the ability to predict when crimes were about to be committed ahead of time, enabling law enforcement to act early.

Twenty years later, in a climate of abundant data, almost limitless processing, and at a point in history where law enforcement is frequently discussed, some of these technologies are beginning to look more feasible than ever.

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You have probably heard of ChatGPT and DALLE-E, a new class of AI-powered software tools that can create new images or write text. The algorithm brings to life any idea you may have by putting together fragments of what it has previously seen — such as images annotated with meta-descriptions of what they represent — to generate original content from user-defined input. But now generative AI technology is revolutionizing drug discovery. Absci Corporation (Nasdaq: ABSI) is using machine learning to transform the field of antibody therapeutics: Absci has put out a press release today announcing the ability to create new antibodies with the use of generative AI.

GenerativeAI: You’ve seen it with images like DALL-E, you’ve seen it with text like ChatGPT. Now you can see it with protein design as well.

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Anthropic, the startup co-founded by ex-OpenAI employees that’s raised over $700 million in funding to date, has developed an AI system similar to OpenAI’s ChatGPT that appears to improve upon the original in key ways.

Called Claude, Anthropic’s system is accessible through a Slack integration as part of a closed beta. TechCrunch wasn’t able to gain access — we’ve reached out to Anthropic — but those in the beta have been detailing their interactions with Claude on Twitter over the past weekend, after an embargo on media coverage lifted.

Claude was created using a technique Anthropic developed called “constitutional AI.” As the company explains in a recent Twitter thread, “constitutional AI” aims to provide a “principle-based” approach to aligning AI systems with human intentions, letting AI similar to ChatGPT respond to questions using a simple set of principles as a guide.

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If all the hype around ChatGPT, Dall-E, Tesla’s Fully Self Driving mode and *ahem* Q.ai, has shown us anything, it’s that artificial intelligence is here to stay. The knee jerk reaction from many old fashioned meat machines, sorry, humans, is a concern around what this means for their income.

For years now, we’ve been told how AI is going to take our jobs, and it’s true that in many industries, machines, robots and other technology have cut workforce numbers dramatically.

With that said, many of the jobs being taken by AI so far are often considered dangerous, repetitive and boring. There aren’t too many people out there who are going to get great job satisfaction from turning the same 5 screws on a production line for 40 hours a week.

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New study demonstrates the potential for machine learning to accelerate the development of innovative drug delivery technologies.

Scientists at the University of Toronto have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster.

The study will be published today (January 10, 2023) in the journal Nature Communications.

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Researchers at DeepMind in London have shown that artificial intelligence (AI) can find shortcuts in a fundamental type of mathematical calculation, by turning the problem into a game and then leveraging the machine-learning techniques that another of the company’s AIs used to beat human players in games such as Go and chess.

The AI discovered algorithms that break decades-old records for computational efficiency, and the team’s findings, published on 5 October in Nature1, could open up new paths to faster computing in some fields.

“It is very impressive,” says Martina Seidl, a computer scientist at Johannes Kepler University in Linz, Austria. “This work demonstrates the potential of using machine learning for solving hard mathematical problems.”

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This post is also available in: he עברית (Hebrew)

New research may have vital applications in areas such as human-intelligence analytics. Traditionally, emotion detection has relied on the assessment of visible signals such as facial expressions, speech, body gestures or eye movements. However, these methods can be unreliable as they do not effectively capture an individual’s internal emotions. A novel artificial intelligence approach based on wireless signals could help to reveal our inner emotions.

The research from Queen Mary University of London demonstrates the use of radio waves to measure heart rate and breathing signals and predict how someone is feeling even in the absence of any other visual cues, such as facial expressions. It demonstrates how to apply a neural network to decipher emotions gathered with transmitting radio antenna.

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