LLMs & Generative AI - Latest AI News & Updates
Latest breakthroughs in large language models and generative AI shaping the future of artificial intelligence and machine learning.
Latest breakthroughs in large language models and generative AI shaping the future of artificial intelligence and machine learning.
Why does a $200 grocery allowance matter in 2026? For many households, the line between nutritious meals and stretching a paycheck is razor‑thin.
Why are new graduates suddenly eyeing AI roles that promise salaries near Rs 22 LPA?
Most retrieval‑augmented generation pipelines still slice PDFs by a fixed number of characters, treating every page as a string of text. That shortcut works for news articles but falls apart when the source is a spec sheet or a wiring manual.
Why does it matter when a large‑language model leans on a single, user‑generated wiki for its answers? While ChatGPT isn’t the only chatbot pulling information from Elon Musk’s Grokipedia, the pattern is emerging across the field.
Moonshot just dropped Kimi K2.5, a 595‑gigabyte language model that touts built‑in support for agent swarms.
AI‑generated clips targeting U.S. Immigration and Customs Enforcement have taken an unexpected turn: they’re being scripted like fan‑fiction.
The startup that sprang from Yann LeCun’s circle is turning heads by questioning the prevailing belief that scaling up large language models will inevitably lead to artificial general intelligence.
When I fed Google’s latest language model a handful of classic Nintendo sprites, the result was… underwhelming. The AI stitched together familiar colors and pixel patterns, but the characters felt hollow, the level design flimsy.
Why does a model that can “zoom” matter for architects and engineers? While most large language models focus on text, Gemini 3 Flash adds a visual twist: it learns to hone in on tiny features without explicit prompts.
Chrome’s latest update nudges the browser into “agentic” AI territory, promising users more proactive assistance while they surf. The rollout arrives as businesses scramble to translate that same technology into concrete profit streams.
The author’s smart‑home setup had become a tangled web of lights, thermostats, cameras and sensors—so many that keeping track felt like cataloguing a small city.
In 2014 a handful of researchers showed that tiny, human‑imperceptible tweaks to a picture could steer an image‑classification model toward a chosen label. The finding sparked a wave of work probing how fragile these systems really are.
Variable‑length sequences have long slowed the training of large language models. When a batch contains sentences of differing lengths, the usual practice is to pad everything to the longest example, wasting compute and memory.
Adaptive6 stepped out of stealth this week with a promise that feels oddly specific in a market crowded with cost‑management buzzwords.
The short film “Send Help” positions itself as a quiet tribute to anyone who’s ever survived a tyrannical supervisor. It opens with Linda, a lone survivor on a deserted shore, navigating the same kind of isolation that a toxic workplace can impose.
Why does this matter? Because the same AI tools that draft emails and answer homework are now being tested for bias that can reinforce hate.
Why does a podcast’s rundown matter to anyone tracking AI’s next moves? Because the LWiAI Podcast’s #232 episode strings together three stories that together sketch a picture of where large‑language‑model companies might be heading.
A sudden freeze swept across Virginia last week, knocking out electricity for tens of thousands. The storm hit just as utilities were already grappling with a surge in power use that the article links to AI‑driven data centers.
The open‑source community has just unveiled a plug‑and‑play toolkit aimed at squeezing an entire video‑generation pipeline into a single forward pass. Its claim?
Google is nudging its search experience toward a conversational layer. The company rolled out AI‑generated Overviews that summarize a query in a few sentences, then lets users drill deeper by typing follow‑up questions.