Artificial intelligence

Artificial intelligence

It's no different with machine learning and large language models. If anything, the open source ecosystem has grown richer and more complex, because now there are open source models to complement the open source code. For article, we've pulled together some of the most intriguing and useful projects for AI and machine learning. Many of these are foundation projects, nurturing their own niche ecology of open source plugins and extensions.

The foundation of an AI strategy is about vision, drivers and risks. It should focus on the essence of what an organization wants to achieve with AI, and be fully aligned with its business strategy. Digital workplace leaders should have regular discussions with relevant stakeholders, including C-level managers. Together, they should identify and formulate a vision that answers the question about the importance of AI to the organization, given its business goals, current market circumstances and competitor activities.

A British AI startup that makes realistic video avatars has almost doubled its valuation to $4bn (3bn), in a boost for the UK technology sector. Synthesia was valued at $2.1bn last year and moved into new offices in central London, marking the moment with a ceremony attended by the Sadiq Khan, the city's mayor, and Peter Kyle, then technology secretary. On Monday, it announced its latest funding round, led by an existing investor, Google Ventures, had raised $200m and valued the British company at $4bn.

"Overly affectionate chatbots, besides being ever-present and readily available, can become hidden architects of our emotional states, thereby invading and occupying the sphere of people's intimacy," the first-ever US-born pope wrote. "All stakeholders - from the technology industry to policymakers, from creative businesses to academia, from artists to journalists and educators - must be involved in building and implementing a conscious and responsible digital citizenship," the pope wrote.

As per the Model Y owner, the vehicle includes a new front camera housing and a 16-inch center display, along with an Autopilot computer labeled "AP45" and part number 2261336-02-A. The Tesla owner later explained that he confirmed the part number by briefly pulling down the upper carpet liner beneath the Model Y's glovebox, a process that requires no tools and exposes the vehicle's Autopilot computer.

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On Friday, the National Transportation Safety Board announced it opened an investigation into the self-driving company over the alarming incidents, and specifically the more than 20 instances reported in Austin, Texas. "Investigators will travel to Austin to gather information on a series of incidents in which the automated vehicles failed to stop for loading or unloading students," the NTSB said in a statement provided to TechCrunch.

Tesla told workers during a town hall last week that it plans to begin collecting data to train its humanoid robot at its Austin Gigafactory, insiders told Business Insider. The company is looking to train Optimus how to operate in the Texas facility, it said, adding that it was targeting a February start date. Tesla has been collecting data and training Optimus prototypes in its Fremont, California, factory for more than a year.

"This has been said a thousand times before, but allow me to add my own voice: the era of humans writing code is over," Dahl wrote. "Disturbing for those of us who identify as SWEs, but no less true. That's not to say SWEs don't have work to do, but writing syntax directly is not it."

AI, like Google Maps, provides the "prediction" of the best route, but the "judgement" of the destination remains with the driver (Author x Gemini) Yet when it comes to using AI for decisions, I see people paralysed by exactly these fears. This ranges from choosing what to study to planning a career move to even planning an article. "Is this cheating?" "Will I lose my critical thinking skills?" or "Am I even thinking for myself anymore?"

If you want to stir up some frothy drama, ask an economist about bubbles. (SOUNDBITE OF ARCHIVED NPR CONTENT) EUGENE FAMA: The word bubble drives me nuts, frankly. GUO: That's Nobel Prize winner Eugene Fama talking to us on the Planet Money podcast back in 2013, when he issued a famous challenge to his fellow economists. Try and predict the next financial bubble.

"It's interesting they've gone for that so early," he said. "Maybe they feel they need to make more revenue."

Now that the dust has settled and AI evolution has become a truth we must all live under, this narrative feels outdated. The agencies that thrive won't be those resisting AI, nor those blindly automating everything in sight, but those that incorporate it, intelligently, in their process. The real opportunity lies not in the battle of human v AI, but in the partnership of human plus AI.

Sports are entering a new era and it could be powered by artificial intelligence. Jeremy Bloom, CEO of the X Games, is placing a bold bet on AI to revolutionize how competitions are judged and scored. From reducing human error to enhancing fairness and accuracy, AI judges could redefine the future of professional sports. But can machines truly replace human judgment on the world's biggest stages?