#large language models

#large language models

AI labs are racing to build data centers as large as Manhattan, each costing billions of dollars and consuming as much energy as a small city. The effort is driven by a deep belief in "scaling" - the idea that adding more computing power to existing AI training methods will eventually yield superintelligent systems capable of performing all kinds of tasks.

There is an all-out global race for AI dominance. The largest and most powerful companies in the world are investing billions in unprecedented computing power. The most powerful countries are dedicating vast energy resources to assist them. And the race is centered on one idea: transformer-based architecture with large language models are the key to winning the AI race. What if they are wrong?

It's fair to say that belief is rarely rational. We organize information into patterns that "feel" internally stable. Emotional coherence may be best explained as the "quiet logic" that makes a story satisfying, somewhat like a leader being convincing or a conspiracy being oddly reassuring. And here's what's so powerful-It's not about accuracy, it's the psychological comfort or even that "gut" feeling. When the pieces fit, the mind relaxes into complacency (or perhaps coherence).

It's a phenomenon tied to the prevalence of text-based apps in dating. Recent surveys show that one in fiveadults under 30 met their partner on a dating app like Tinder or Hinge, and more than half are using dating apps. For years, app-based dating has been regarded as a profoundly alienating experience, a paradigm shift which coincides with a rapid rise in social isolation and loneliness.

His reward for going along with those demands, after being a faithful servant for 17 years at the edutech company? Getting replaced by a large language model, along with a couple dozen of his coworkers. That's, of course, after his boss reassured him that he wouldn't be replaced with AI. Deepening the bitter irony, Cantera - a researcher and historian - had actually grown pretty fond of the AI help, telling WaPo that it "was an incredible tool for me as a writer."

The late English writer Douglas Adams is best known as the author of the 1979 book The Hitchhiker's Guide to the Galaxy. But there is much more to Adams than what is written in his Wikipedia entry. Whether or not you need to know that his birth sign is Pisces or that libraries worldwide store his books under the same string of numbers - 13230702 - you can if you head to an overlooked corner of the Wikimedia Foundation called Wikidata.

If you're here, you're likely asking: "Where can AI really make a difference in my day-to-day work, without compromising quality or trust?" We understand that when your service business is built on deep expertise, judgment calls, and tight deadlines, the answer can make or break your operations. That's why, in this blog post, we'll show you concrete use cases of AI in professional services industry, from consulting analysis to legal research, financial auditing, and client delivery.

Despite what watching the news might suggest, most people are averse to dishonest behavior. Yet studies have shown that when people delegate a task to others, the diffusion of responsibility can make the delegator feel less guilty about any resulting unethical behavior. New research involving thousands of participants now suggests that when artificial intelligence is added to the mix, people's morals may loosen even more.

Cybersecurity veteran Brian Gumbel - president and chief operating officer (COO) at Dataminr - works at the confluence of real-time information and AI. Mainlined into humanity's daily maelstrom of data, Dataminr detects events "on average 5 hours ahead of the Associated Press" - it picked up the 2024 Baltimore bridge collapse, for example, about an hour ahead of all mainstream media sources. The accuracy rate of its "news" is, says Gumbel, a highly impressive 99.5%.

"I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people."

Researchers took a stripped-down version of GPT-a model with only about two million parameters-and trained it on individual medical diagnoses like hypertension and diabetes. Each code became a token, like a word in the sentence of a prompt, and each person's medical history became a story unfolding over time. For a little context, GPT-4 and GPT-5 are believed to have hundreds of billions to trillions of parameters, making them hundreds of thousands of times larger than this small model.

GAIA is revolutionising the legal industry with AI that automates legal work and empowers legal professionals to work more efficiently and effectively. We're building the future of legal technology, and we are looking for a driven, versatile person to help accelerate our growth. The Role As we scale, we're looking for an exceptional Product Engineer who's passionate about experimenting with large language models (LLMs), turning ideas into working prototypes, and pushing the boundaries of how AI transforms knowledge-heavy industries.

For decades, public relations agencies controlled the gatekeeping process between brands and media. Companies relied on bloated retainers, traditional press kits, and personal connections to get coverage. But that model is fading fast. Today, anyone with an internet connection can leverage AI to create compelling press releases, distribute them on platforms like PRWeb, and pitch journalists directly-often faster, cheaper, and with more precision than legacy firms.

People are starting to "talk like AI," according to OpenAI CEO Sam Altman. While teachers and business leaders complain about people using AI chatbots to write and communicate - and more and more public figures use AI-controlled avatars to communicate on their behalf - even authentic human speech is starting to sound "fake" and "machine-like," according to Altman, who posted his views Monday on X.

Paid media has always been about positioning-brands spending strategically to reach audiences where they live, scroll, and search. But the definition of "visibility" is shifting. Today, being seen is no longer limited to ad placements, keyword bidding, or social media impressions. Artificial intelligence has become the new filter through which information is discovered, recommended, and trusted. The rise of large language models (LLMs) like ChatGPT, Perplexity, and Claude, combined with real-time indexing from Google and Apple News, has changed how people interact with content.