Serverless Inference with Together AI
Together AI serverless inference for text generation, image generation, and vision language models along with Gradio chat application.| DebuggerCafe
The rapid advancements in Artificial Intelligence (AI), particularly the ascent of Large Language Models (LLMs), have sparked widespread discussion about their potential to revolutionize various industries. Within network operations, where vast volumes of time-series data are generated continuously, there is a natural curiosity about whether LLMs can significantly enhance, or even replace, established analytical methods … continue reading The post Network Time-Series Analysis Beyond the LLM...| ITOps Times
Large Language Models can be backdoored by introducing just a limited number of “poisoned” documents during their training, say researchers.| The Stack
When the peer-to-peer site Napster unleashed digital audio on the web, the record industry couldn’t move fast enough. It took about a year and a half for the first major lawsuit to shut the service down. The battle was won, but the war for control over music distribution was irrevocably lost. Today, the publishing industry […] The post Stop Debating And Start Acting: A Unified Front Against AI Is Publishers’ Only Hope appeared first on AdExchanger.| AdExchanger
In this article, we create a multimodal Gradio application with Together AI models for chatting LLMs & VLMs, generating images, and automatic speech transcription using OpenAI Whisper models. The post Multimodal Gradio App with Together AI appeared first on DebuggerCafe.| DebuggerCafe
Together AI serverless inference for text generation, image generation, and vision language models along with Gradio chat application.| DebuggerCafe
Imagine this: You ask your company’s AI a simple question and it answers with absolute confidence. But what if that answer is wrong, outdated, or completely irrelevant? In business, where every decision can have financial or reputational consequences, this isn’t just inconvenient. It’s dangerous. One of the biggest concerns holding companies back from using Generative […]| SEEBURGER Blog
Today's links The billionaires aren't OK: They're going to give us all Howard Hughes disease. Hey look at this: Delights to delectate. Object permanence: KY Republican says the First Amendment protects bribes; Walt Disney's FBI; "The Sapling Cage." Upcoming appearances: Where to find me. Recent appearances: Where I've been. Latest books: You keep readin' em, I'll keep writin' 'em. Upcoming books: Like I said, I'll keep writin' 'em. Colophon: All the rest. The billionaires aren't OK (permalink...| Pluralistic: Daily links from Cory Doctorow
The emergence of AI agents will transform how we think about digital experiences. Discover how Agentic Responsive Design will change the web.| AI Accelerator Institute
Discover how Grammarly’s AI-powered communication, personalization, and AI agents are reshaping the future of writing and collaboration.| AI Accelerator Institute
Chat with videos and get precise timestamps.| Daily Dose of Data Science
..powered with MCP + Tools + Memory + Observability.| Daily Dose of Data Science
TL;DR The digital landscape is rapidly evolving with Large Language Models (LLMs) reshaping content discovery and consumption. As AI-driven platforms like ChatGPT and Google’s AI … The post Content Revamp: How Updating Old Content Boosts Performance with LLMs appeared first on Smarketers.| Smarketers
I did some digging to track down the librarian I learned about on a thrift store postcard.| librarian.net
Cursor is an AI-focused VS Code fork. Here's Steve Kinney with a nice overview of what it offers and how to start getting help out of it right away.| frontendmasters.com
Explore how the Active Agent library brings Rails conventions to AI development, with real-world examples from Evil Martians' early adoption experience| evilmartians.com
Discover how WPI, HaystackID®, and Relativity® partnered to test LLMs, build AI prototypes, and advance legal tech innovation. The post [Webcast] How Academic-Centric AI Projects are Driving Legal Tech R&D (November 19, 2025) appeared first on HaystackID.| HaystackID
This video breaks down how agentic AI functions, its potential to revolutionize business operations, and the vulnerabilities it introduces.| Help Net Security
LLMs in cybersecurity can boost decision accuracy, but uneven benefits and automation bias mean teams must verify outputs.| Help Net Security
If you’re trying to make sense of how to build AI agents, not just talk about them, AI Agents in Action might be for you—read the review.| Help Net Security
I’ve noticed something interesting over the past few weeks: I’ve started using the term “agent” in conversations where I don’t feel the need to then define it, roll my eyes …| Simon Willison’s Weblog
More from Mike Caulfield (see also the SIFT method). He starts with a fantastic example of Google's AI mode usually correctly handling a common piece of misinformation but occasionally falling …| Simon Willison’s Weblog
Avoid costly LLM pitfalls: Learn how token pricing, scaling costs, and strategic prompt engineering impact AI expenses—and how to save.| AI Accelerator Institute
All you need to know about Qwen 3 Max by Alibaba. China's most powerful AI with 1 trillion parameters, long context, and top benchmark scores.| Fello AI
Learn how Enriched SaaS App Intelligence can strengthen SaaS and AI Risk Management with classification, risk scoring, and AI app coverage. The post SaaS Risk Management for Vendors in the Age of AI appeared first on zvelo.| zvelo
Over the past months, I've been working on a project that combines my interests in data-engineering, AI, and civic transparency: building a [Contextualise AI](posts/contextualise-ai/)-based data pipeline that processes and analyses the procedures of the Norwegian Parliament (Stortinget).| Brett Kromkamp
In this article, we explore deploying LLMs using Runpod, Vast.ai, Docker, and Hugging Face Text Generation Inference. The post Deploying LLMs: Runpod, Vast AI, Docker, and Text Generation Inference appeared first on DebuggerCafe.| DebuggerCafe
Optimize your Shopify store content for AI and LLMs with these expert techniques. Learn steps to boost visibility, from structured data to more.| StoreSEO
Worldcon is the apex annual convention for a certain stratum of science fiction fandom. My stratum, to be precise. It's also the conference whose members vote the annual Hugo Awards. Sadly, Worldcon the conference is becoming less notable than ...| Zarf Updates
This article serves as a primer on prompt engineering, delving into the array of techniques used to control LLMs.| AI Accelerator Institute
Discover expert insights on how to secure LLMs with the fastest guardrails in the industry, ensuring AI performance, safety, and reliability at scale.| AI Accelerator Institute
KT and Viettel will work to develop a Vietnamese AI language model, creating industry-specific AX platforms.| RCR Wireless News
Frontier model training has pushed GPUs and AI systems to their absolute limits, making cost, efficiency, power, performance per TCO, and reliability central to the discussion on effective training. The Hopper vs Blackwell comparisons are not as simple as Nvidia would have you believe. In this report, we will start by present the results of […]| SemiAnalysis
To many power users (Pro and Plus), GPT5 was a disappointing release. But with closer inspection, the real release is focused on the vast majority of ChatGPT’s users, which is the 700m+ free userbase that is growing rapidly. Power users should be disappointed; this release wasn’t for them. The real consumer opportunity for OpenAI lies […]| SemiAnalysis
Researchers say Chain-of-Thought reasoning in AI is mostly pattern-matching, not real logic, and fails outside training.| Digital Information World
Open-Source Large Language Models in Radiology| vitalab.github.io
Discover the hidden bias in how humans evaluate AI outputs! Learn how perceptions of procedural knowledge extraction shape trust in AI and explore pathways to bridge the human-AI divide.| Blue Headline
I shipped LLM 0.27 today (followed by a 0.27.1 with minor bug fixes), adding support for the new GPT-5 family of models from OpenAI plus a flurry of improvements to …| Simon Willison’s Weblog
With GenAI and LLMs comes great potential to delight and damage customer relationships—both during the sale, and in the UI/UX. How should AI company founders and product leaders adapt? The post Designing and Selling Enterprise AI Products [Worth Paying For] first appeared on Designing for Analytics (Brian T. O'Neill).| Designing for Analytics (Brian T. O'Neill)
Discover BlindChat, an open-source privacy-focused conversational AI that runs in your web browser, safeguarding your data while offering a seamless AI experience. Explore how it empowers users to enjoy both privacy and convenience in this transformative AI solution.| Mithril Security Blog
Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and search engines to code generators and creative writing assistants. Yet behind every seemingly effortless AI conversation lies a sophisticated multi-stage modeling process that transforms raw text into intelligent, task-specific systems capable of human-like understanding and generation. Understanding the LLM modeling stages described later in this blog is crucial to be able...| Analytics Yogi
Has anyone staged an intervention for Tracie Harris? [12:29] THEO: Uh, yeah. Let’s talk about it. First off, for your listeners, hi, I’m Theo. I’m not a persona. This isn’t …| Reprobate Spreadsheet
This might be beating a dead horse, but there are several "mysterious" problems LLMs are bad at that all seem to have the same cause. I wanted an article I could reference when this comes up, so I wrote one. LLMs can't count the number of R's in strawberry. LLMs …| Brendan Long
Future of Sex checks out what might happen when AI developers can no longer "look under the hood" of our erotic chatbot companions| Future of Sex
I spent the past ~4 weeks trying out all the new and fancy AI tools for software development.| Tolki's Blog
I gave a talk on Wednesday at the Bay Area AI Security Meetup about prompt injection, the lethal trifecta and the challenges of securing systems that use MCP. It wasn’t …| Simon Willison’s Weblog
I’ve been dipping into the r/ChatGPT subreddit recently to see how people are reacting to the GPT-5 launch, and so far the vibes there are not good. This AMA thread …| Simon Willison’s Weblog
I’ve had preview access to the new GPT-5 model family for the past two weeks (see related video and my disclosures) and have been using GPT-5 as my daily-driver. It’s …| Simon Willison’s Weblog
In this article, we build a simple video summarizer application using Qwen2.5-Omni 3B model with the UI powered by Gradio. The post Video Summarizer Using Qwen2.5-Omni appeared first on DebuggerCafe.| DebuggerCafe
Fine-tuning SmolLM2-135M Instruct model on the WMT14 French-to-English subset for machine translation using a small language model.| DebuggerCafe
AI Agents Crash Course—Part 8 (with implementation).| Daily Dose of Data Science
While the peer review process is the bedrock of modern science, it is notoriously slow, subjective, and inefficient. This blog post explores how Large Language Models (LLMs) can be used to re-imagine the review architecture, augmenting human expertise to build a system that is faster, more consistent, and ultimately more insightful. A New Architecture: The […]| SIGARCH
Editor’s note: With continuing proliferation of LLMs and their capabilities, academic community started to discuss their potential role in paper reviewing process. Some conferences are already piloting the assistance of LLMs in their reviewing this year. To bring this discussion to the attention of our community, “Computer Architecture Today” is publishing two related blog posts. […]| SIGARCH
With all the recent hype around large language models (LLMs) and their ability to effortlessly generate code, Pedro Tavares reminds us that it’s worth reflecting on a common misconception, namely writing code was never the bottleneck in software development. If we forget this, we risk assuming code quality rather than ensuring it.| Looking for data in all the right places...
This is the second in a trial blog series called “Practically Prompted” – an experiment in using large language models to independently select a recent, ethically rich news story and then write a Practical Ethics blog-style post about it. The text below is the model’s work, followed by some light human commentary. See this post for the… Read More »Practically Prompted #2 – Regulating the Regulators: Europe’s New AI ‘Code of Practice’ and the Ethics of Voluntary Complianc...| Practical Ethics
Discover how the NHS’s GOSH is using large language models and AI to transform pediatric healthcare, improving outcomes for rare disease treatments.| AI Accelerator Institute
Some people can get an AI assistant to write a day’s worth of useful code in ten minutes. Others among us can only watch it crank out hundreds of lines of crap that never works. What’s the difference? The post Will AI Speed Development in Your Legacy App? appeared first on Honeycomb.| Honeycomb
I’m pleased to announce the public beta of Honeycomb Hosted MCP, along with our first wave of one-click integrations for Cursor, Visual Studio Code, and Claude Desktop. We’re also very excited to announce that Hosted MCP is available on AWS AI Agents marketplace and for all Honeycomb plans (including our free plan!) at no charge. The post Honeycomb In Your IDE? Yes, With Hosted MCP Now Available in AWS Marketplace AI Agents and Tools Category appeared first on Honeycomb.| Honeycomb
What happens when a clinical AI tool strays from clinical data? Our team ran the experiments—and ended up with chocolate chip cookies. That’s a problem.| Eleos Health
Qwen3, the latest LLM in the Qwen family uses a unified architecture for thinking and non-thinking mode, using the same LLM for reasoning.| DebuggerCafe
For years, I’ve relied on a straightforward method to identify sudden changes in model inputs or training data, known as “drift.” This method, Adversarial Validation1, is both simple and effective. The best part? It requires no complex tools or infrastructure. Examples where drift can cause bugs in your AI: Your data for evaluations are materially different from the inputs your model receives in production, causing your evaluations to be misleading. Updates to prompts, functions, RAG, a...| Hamel's Blog
Motivation Axolotl is a great project for fine-tuning LLMs. I started contributing to the project, and I found that it was difficult to debug. I wanted to share some tips and tricks I learned along the way, along with configuration files for debugging with VSCode. Moreover, I think being able to debug axolotl empowers developers who encounter bugs or want to understand how the code works. I hope this document helps you get started. This content is now part of the Axolotl docs! I contributed t...| Hamel's Blog
The worrying thing is that the new OpenAI models, both the o3 and the o4-mini, generate more hallucinations than ever compared to previous models.| Techoreon
This is the first in a trial blog series called “Practically Prompted” – an experiment in using large language models to independently select a recent, ethically rich news story and then write a Practical Ethics blog-style post about it. The text below is the model’s work, followed by some light human commentary. See this post… Read More »Practically Prompted #1: Should We Screen the Womb? Ethical Questions Raised by the New Miscarriage-Risk Test The post Practically Prompted #1: ...| Practical Ethics
This post introduces a trial blog series called “Practically Prompted” – an experiment in using large language models (LLMs) to write a Practical Ethics blog-style post, with some light human commentary about the output. So, why try this? The experiment is driven by several key motivations: To Test a New Tool: We want to see| Practical Ethics
Discover how to boost LLM performance and output quality with exclusive tips from Capital One’s Divisional Architect.| AI Accelerator Institute
Claude Code added OpenTelemetry metric and log support in a recent release, which led Austin to ask, can Claude Code observe itself?| Honeycomb
I was tinkering on some image models with my buddy Sahil the other day. He is an AI engineer who can make these AI systems do crazy things. He's also the ...| inspired by rebels
A curated collection of links, books, tools, and benchmarks discussed during the February 2nd, 2025 Twitter/X Audio Space on LLMs and AI. Includes practical resources, RAG leaderboards, toolkits, and perspectives on AI adoption in the Middle East and globally.| Osman's Odyssey: Byte & Build
Quick observations on the latest AI startup products.| An Operator's Blog
New research from Apple says large reasoning models collapse under pressure – challenging the AGI concept, and exposing AI industry overreach.| RCR Wireless News
We all know that the Web is currently under attack by AI companies trying to turn scraped data into venture capital. I'd link to the early article I saw sounding the alarm, but I can't find it because there are hundreds of search hits on "ai ...| Zarf Updates
An exploration of what turns a language model into an agent — memory, goals, tools, and the quiet architecture of intent.| too long; automated
I previously tried (and failed) to setup LLM tracing for hinbox using Arize Phoenix and litellm. Since this is sort of a priority for being able to follow along with the Hamel / Shreya evals course with my practical application, I’ll take another stab using a tool with which I’m familiar: Braintrust. Let’s start simple and then if it works the way we want we can set things up for hinbox as well. Simple Braintrust tracing with litellm callbacks Callbacks are listed in the litellm docs as...| Alex Strick van Linschoten
It’s important to instrument your AI applications! I hope this can more or less be taken as given just as you’d expect a non-AI-infused app to capture logs. When you’re evaluating your LLM-powered system, you need to have capture the inputs and outputs both at an end-to-end level in terms of the way the user experiences things as well as with more fine-grained granularity for all the internal workings. My goal with this blog is to first demonstrate how Phoenix and litellm can work toget...| Alex Strick van Linschoten
I’ve been working on a project called hinbox - a flexible entity extraction system designed to help historians and researchers build structured knowledge databases from collections of primary source documents. At its core, hinbox processes historical documents, academic papers, books and news articles to automatically extract and organize information about people, organizations, locations, and events. The tool works by ingesting batches of documents and intelligently identifying entities ac...| Alex Strick van Linschoten
Explore the leap from Large Language Models to Large Action Models, unveiling a new era in AI that transcends text to understand a world of data.| AI Accelerator Institute
Solomon Hykes just presented the best definition of an AI agent I've seen yet, on stage at the AI Engineer World's Fair: An AI agent is an LLM wrecking its …| Simon Willison’s Weblog
A fun new benchmark just dropped! Inspired by the Claude 4 system card—which showed that Claude 4 might just rat you out to the authorities if you told it to …| Simon Willison’s Weblog
DeepSeek released an updated version of their popular R1 reasoning model (version 0528) with – according to the company – increased benchmark performance, reduced hallucinations, and native support for function calling and JSON output. Early tests from Artificial Analysis report a nice bump in performance, putting it behind OpenAI’s o3 and o4-mini-high in their Intelligence| www.macstories.net
Over the course of my career, I’ve had three distinct moments in which I saw a brand-new app and immediately felt it was going to change how I used my computer – and they were all about empowering people to do more with their devices. I had that feeling the first time I tried Editorial,| www.macstories.net
Let the LLM 'contemplate' before answering| Maharshi's blog
As AI becomes embedded in daily business workflows, the risk of data exposure increases. CISOs cannot treat this as a secondary concern.| Help Net Security
A discussion on techniques available to overcome semantic errors in syntax when generating dialect-specific SQL| Gavin Ray Blog
A from-scratch implementation of Llama 4 LLM, a mixture-of-experts model, using PyTorch code.| Daily Dose of Data Science
AI Agents Crash Course—Part 14 (with implementation).| Daily Dose of Data Science
Big upgrade to Mistral's API this morning: they've announced a new "Agents API". Mistral have been using the term "agents" for a while now. Here's how they describe them: AI …| Simon Willison’s Weblog
I was going slightly spare at the fact that every talk at this Anthropic developer conference has used the word "agents" dozens of times, but nobody ever stopped to provide …| Simon Willison’s Weblog
Classic slop: it listed real authors with entirely fake books. There's an important follow-up from 404 Media in their subsequent story: Victor Lim, the vice president of marketing and communications …| Simon Willison’s Weblog
I’m tired of this phrase and this simple way of thinking about tools. This blog post is a wandering train of thought on the topic of what tools are and why it matters to be even slightly more mature in how we think about them.| Frank Elavsky
If you’re an enterprise leader staring down ballooning tech debt, rising pressure for AI transformation, and daily new product drops...| Horses for Sources | No Boundaries
I came across this quote in a happy coincidence after attending the second session of the evals course: It’s obviously a bit abstract, but I thought it was a nice oblique reflection on the topic being discussed. Both the main session and the office hours were mostly focused on the first part of the analyse-measure-improve loop that was introduced earlier in the week. Focus on the ‘analyse’ part of the LLM application improvement loop It was a very practical session in which we even took...| Alex Strick van Linschoten
Key insights from the first session of the Hamel/Shreya AI Evals course, focusing on a 'three gulfs' mental model (specification, generalisation, and comprehension) for LLM application development…| mlops.systems
Introducing PGN2FEN — a benchmark for evaluating language models' ability to understand and transcribe chess game move sequences.| Aidan Cooper
Why conversational interfaces still aren't the right approach for human-computer interaction.| colemanm.org
If this is what you think working with a junior is like, you probably suck at mentoring| avdi.codes
Qwen2.5-VL is the newest member in the Qwen Vision Language family, capable of image captioning, video captioning, and object detection.| DebuggerCafe
AI Agents Crash Course—Part 13 (with implementation).| Daily Dose of Data Science
