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SAN FRANCISCO—At its Code with Claude developers’ conference, Anthropic has introduced what it calls “dreaming” to Claude Managed Agents. Dreaming in this case is a process of going over recent events and identifying specific things that are worth storing in “memory” to inform future tasks and interactions. Dreaming is a feature that is currently in […]
Anthropic’s Claude Managed Agents can now “dream,” sort of Read More »
Why it matters: What is tokenization in NLP? A complete guide covering subword tokenization, BPE, WordPiece, transformer token limits, and modern LLM applications.
What is Tokenization in NLP? Read More »
LLM Evaluation with Domain Experts: The Complete Guide for Enterprise Teams Table of Contents Download eBook Get My Copy If your company has started using AI tools that generate text — chatbots, document summarizers, policy assistants, or customer service bots — you have probably asked yourself: “How do we know the AI is actually giving
LLM Evaluation with Domain Experts: The Complete Guide for Enterprise Teams Read More »
RPA (robotic process automation) is a practical and proven way to reduce manual work in business processes without AI systems. By using software bots to follow fixed rules, companies can automate repetitive tasks like data entry and invoice processing, and to a certain extent, report generation. Adoption grew quickly in many sectors, especially in finance,
RPA matters, but AI changes how automation works Read More »
A nagging question remains after asking, “What’s next after zero-click search?” How do frontier models – like OpenAI’s o3 series or Google’s Gemini 3 – learn? Garbage in, garbage out Large language models (LLMs) learn from massive amounts of text data, including billions of words, public information, and, you guessed it, […] The post The hunt
The hunt for (Reddit) data is over Read More »
If you’ve been using the Internet for any length of time, you’ve probably used a tool like Google Translate to convert webpages or snippets of text to and from languages ranging from Uzbek to Esperanto. But what if you want to translate into more esoteric “languages” like “LinkedIn Speak,” “Gen Z slang,” or “horny Margaret
Kagi Translate’s AI answers the question “What would horny Margaret Thatcher say?” Read More »
Meta has acquired Moltbook, the Reddit-esque simulated social network made up of AI agents that went viral a few weeks ago. The company will hire Moltbook creator Matt Schlicht and his business partner, Ben Parr, to work within Meta Superintelligence Labs. The terms of the deal have not been disclosed. As for what interested Meta
Meta acquires Moltbook, the AI agent social network Read More »
Following backlash in a Hacker News thread, Microsoft deleted a blog post that critics said encouraged developers to pirate Harry Potter books to train AI models that could then be used to create AI slop. The blog, which is archived here, was written in November 2024 by a senior product manager, Pooja Kamath. According to
Microsoft deletes blog telling users to train AI on pirated Harry Potter books Read More »
On Thursday, Google announced that “commercially motivated” actors have attempted to clone knowledge from its Gemini AI chatbot by simply prompting it. One adversarial session reportedly prompted the model more than 100,000 times across various non-English languages, collecting responses ostensibly to train a cheaper copycat. Google published the findings in what amounts to a quarterly
Attackers prompted Gemini over 100,000 times while trying to clone it, Google says Read More »
What adversarial prompt generation means Adversarial prompt generation is the practice of designing inputs that intentionally try to make an AI system misbehave—for example, bypass a policy, leak data, or produce unsafe guidance. It’s the “crash test” mindset applied to language interfaces. A Simple Analogy (that sticks) Think of an LLM like a highly capable
Adversarial Prompt Generation: Safer LLMs with HITL Read More »
