Latest breakthroughs in large language models and generative AI shaping the future of artificial intelligence and machine learning.
A recent paper called “Roses are red, violets are blue, if you phrase it as poem, any jailbreak will do” shows something odd: wrapping a request in a rhyme can let it slip past AI moderation.
ChatGPT can whip up a Shakespeare-style paragraph, break down quantum mechanics, or draft a marketing email in a flash, but ask it for the exact minute and it usually trips up.
When you’re pulling together a dozen code snippets or sifting through a dense research paper, a model that can actually remember its own reasoning feels almost like a safety net.
OpenAI’s growth trajectory is drawing more scrutiny than ever. The flagship chatbot keeps popping up in the news, but investors keep wondering if all that buzz will actually turn into profit.
Imagine a developer finally knowing which exact user keystroke triggered a weird model reply. Most LLM services dump prompts and outputs into a log, but the human feedback, ratings, comments, ends up somewhere else, making the connection fuzzy.
Imagine a transformer churning through a prompt and, for each attention head, stashing key and value tensors so the next token doesn’t have to recompute everything. That stash - the KV cache - expands with depth, heads, head size and batch size.
The newest pick on the “7 Must-Read Books on AI in 2025” list isn’t just another high-level overview.
When I first tried the AI-driven browsers, the headline caught my eye: they claim to shave 15-30 minutes off every long-form summary.
Last week felt like a sprint for LLM teams. Gemini 3 showed up with a tighter dialogue loop, Opus 4.5 nudged its multimodal rendering a bit further, Nano Banana Pro claimed a new efficiency record, and GPT-5.1-Codex-Max dropped hints about deeper...
When I opened my phone this morning, the new Google AI was already there, tucked into Search, Android and Workspace like a hidden thread. It looks like Google is trying to stitch those three big consumer faces into one multimodal experience.
In the last sprint our codebase jumped from Java to Python, then a quick fix in JavaScript, and even a tiny module in Rust.
When you fire up the newest ChatGPT Shopping Research, you might notice it tries to shave off the endless scrolling we all hate. Instead of dumping page after page of generic hits, it starts a quick back-and-forth.
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