Is A.I. Actually a Bubble? The narrative of boom and bust is familiar--but also out of step with the possibilities of a new technology. Over the past few months, I've introduced artificial intelligence into the hobby life of my seven-year-old son, Peter. On Saturdays, he takes a coding class, in which he recently made a version of rock-paper-scissors, and he really wants to make more sophisticated games at home. I gave ChatGPT and Claude a sense of his skill level, and they instantaneously suggested next steps. Claude proposed trying to recreate Pong in Scratch, a coding environment for kids.

It may have its roots in science fiction, but a small number of researchers are making real progress trying to create computers out of living cells. Welcome to the weird world of biocomputing. Among those leading the way are a group of scientists in Switzerland, who I went to meet. One day, they hope we could see data centres full of living servers which replicate aspects of how artificial intelligence (AI) learns - and could use a fraction of the energy of current methods. That is the vision of Dr Fred Jordan, co-founder of the FinalSpark lab I visited.

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. As a classically trained singer preparing for a professional career, Erin Perry can see quite clearly how artificial intelligence is upending her field--all the way down to the classroom. Perry just completed her first year as a graduate student in voice performance at the Peabody Institute, the prestigious music conservatory run by Johns Hopkins University. It's been rewarding so far: She's been learning how to navigate the modern classical music sector and confronting the relevant impacts of generative A.I., having taken on a project to study the major record labels' lawsuit against the Amazon-backed A.I. startup Anthropic, which trained its models on songwriters' lyrics sans permission or compensation. Understandably, Perry's rather skeptical of A.I.'s artistic applications, and fearful of the sweeping effects it could have on her chosen field, especially as generative-music startups like Suno and Udio are programmed to replicate specific artists and musical styles.

In vivo image-guided multi-pipette patch-clamp is essential for studying cellular interactions and network dynamics in neuroscience. However, current procedures mainly rely on manual expertise, which limits accessibility and scalability. Robotic automation presents a promising solution, but achieving precise real-time detection of multiple pipettes remains a challenge. Existing methods focus on ex vivo experiments or single pipette use, making them inadequate for in vivo multi-pipette scenarios. To address these challenges, we propose a heatmap-augmented coarse-to-fine learning technique to facilitate multi-pipette real-time localisation for robot-assisted in vivo patch-clamp. More specifically, we introduce a Generative Adversarial Network (GAN)-based module to remove background noise and enhance pipette visibility. We then introduce a two-stage Transformer model that starts with predicting the coarse heatmap of the pipette tips, followed by the fine-grained coordination regression module for precise tip localisation. To ensure robust training, we use the Hungarian algorithm for optimal matching between the predicted and actual locations of tips. Experimental results demonstrate that our method achieved > 98% accuracy within 10 {\mu}m, and > 89% accuracy within 5 {\mu}m for the localisation of multi-pipette tips. The average MSE is 2.52 {\mu}m.

An AI weather program running for a single second on a desktop can match the accuracy of traditional forecasts that take hours or days on powerful supercomputers, claim its creators. Weather forecasting has, since the 1950s, relied on physics-based models that extrapolate from observations made using satellites, balloons and weather stations. But these calculations, known as numerical weather prediction (NWP), are extremely intensive and rely on vast, expensive and energy-hungry supercomputers. Microsoft has a new quantum computer – but does it actually work? In recent years, researchers have tried to streamline this process by applying AI.

On Tuesday, lawmakers, A.I. experts, and the guy chiefly responsible for ChatGPT gathered in the same room to swap analogies for just how dramatically A.I. is about to change our lives. The invention of the internet, the cell phone, and airplanes all made the list. For a Senate Judiciary Committee hearing ostensibly concerned with the dangers A.I. might pose to the world, everyone seemed to get along quite well. At one point Sen. John Kennedy of Louisiana asked Sam Altman, the CEO of ChatGPT maker OpenAI, if he could recommend some people to oversee a new agency to oversee A.I.--that is, to pick his own regulators. Then again, Altman was doing an exceptional job projecting a self-critical persona.

Built through the acquisition of 17 companies over approximately a 4-year timespan, the company has seen continued solid organic growth from their customers in their target markets of healthcare and consumer packaged goods and continues on their new customer acquisition journey. Westfall's corporate methodologies backed by their "Stacked Integration Model" certainly delivers as it relates to their value proposition but also has magnified the need for continuous improvement in key areas given its growth. This has resulted in a corporate structure which poses unique and nuanced supply chain challenges. The company provides end-to-end manufacturing capabilities, including product design, moldmaking, injection molding, assembly and more to a broad range of customers, and as David Schultz, VP, Chief Supply Chain Executive puts it, Westfall Technik counts "all the biggest logos" amongst its customers. Schultz, whose past experience includes several senior operating positions, more specifically, Chief Procurement Officer/Chief Supply Chain Officer for both private and publicly traded companies.

Harnessing artificial intelligence and machine learning technologies has become the new arms race among the great powers, a Hudson Institute panel on handling big data in military operations said Monday. Speaking at the online forum, Richard Schultz, director of the international security program in the Fletcher School at Tufts University, said, "that's the way [Russian President Vladimir] Putin looks at it. I don't think we have a choice" but to view it the same way. He added in answer to a question that "the data in information space is enormous," so finding tools to filter out what's not necessary is critical. U.S. Special Operations Command is already using AI to do what in the old days was called political or psychological warfare, in addition to targeting, he added.

Whether it's reading about Harry Potter or Percy Jackson, sixth grader Lulu Schultz can easily spend an hour diving into an adventure. She does," said Katie Schultz, Lulu's mother. "But I think she's a little insecure about reading out loud, but she loves to read." The road to literacy has been bumpy. Schultz said there were signs Lulu was struggling as far back as second grade.

Harnessing artificial intelligence and machine learning technologies has become the new arms race among the great powers, a Hudson Institute panel on handling big data in military operations said Monday. Speaking at the online forum, Richard Schultz, director of the international security program in the Fletcher School at Tufts University, said, "that's the way [Russian President Vladimir] Putin looks at it. I don't think we have a choice" but to view it the same way. He added in answer to a question that "the data in information space is enormous," so finding tools to filter out what's not necessary is critical. U.S. Special Operations Command is already using AI to do what in the old days was called political or psychological warfare, in addition to targeting, he added.