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How do you handle trying new models without spending too much?
New models pop up constantly—Qwen 3.7, Gemini 3.5 flash, etc. Every time a better one launches, I want to have a try, but I don't want to increase subscriptions. Curious how you all approach this: Stick with what you already subscribe to? Use API platforms to test before committing? Subscribe individually as needed? Waiting for others' reviews? Keeping up with new models seems to be its own expense/workflow now. What's your strategy for balancing access vs. cost? submitted by /u/Ok-Mark8538 [link] [comments]
The AI Era Is Creating a Bug Hunting Arms Race
New to agents, mcp , etc how do I get to a point where i can lay back and let my agents do the work
General AI
I tracked 47 new agent products launched in 2026. Here are 5 ways they differ from the last generation (chart inside)
Inclusion criteria: agent products that emerged in 2026 (excluding major updates to incumbent products from big labs). Sources: TechCrunch, Product Hunt, YC W26 batch, a16z portfolio, AI product newsletters, and Reddit discussions. Between January and May this year, the most interesting product launches in AI came from agents rather than from the foundation models themselves. I put together a list of 47 new agent products from this period, along with 5 observations comparing them to the previous wave (Devin, Operator, early Manus, etc. from 2025). The table # Product When Form factor Generational trait One liner 1 Mem0 Late 2025 / 2026 funding Memory infra ① Compounds Memory infra for agents, 41k+ GitHub stars 2 Nyne Mar 2026, $5.3M seed Context infra ① Compounds Stitches LinkedIn / IG / public records into a unified "who is this user" layer 3 AllyHub 2026 launch Chat to browser ① Compounds Browser agent that learns from each task, branded around the "compounds" idea
Two Paths to Growth: Johnson & Johnson vs AbbVie
Johnson & Johnson (NYSE:JNJ) and AbbVie (NYSE:ABBV) both posted Q1 2026 results that beat revenue expectations and prompted raised full-year guidance. JNJ leaned on a diversified pharma plus MedTech engine. AbbVie leaned almost entirely on immunology. Both face biosimilar headwinds, yet each chose a different way to outgrow them. TREMFYA and Cardiovascular Carry JNJ. Skyrizi ... Two Paths to Growth: Johnson & Johnson vs AbbVie
‘Nobody knows anything’ and ‘this time is different’: the phrases that define — and haunt — the AI economy
Wharton's Ethan Mollick said he talks to AI labs and CEOs all the time, and "anyone who's like, 'We have the playbook'—they're lying to you."
Posthaste: Worried about a market bubble? You ain't seen nothing yet, warns top BofA strategist
Bubble brewing that rivals the roaring '20s, but bulls won't sell until these two things happen
Just wanted to show off how cool I think it is that my python ai has a real brain looking brain
Not promoting or anything, just think it's oddly interesting. submitted by /u/Glittering_Focus1538 [link] [comments]
Missed the First AI Wave? These 3 Stocks Are Still Genius Picks
We're still in the early laps of the AI race.
This Billionaire Dumped Cloud Stocks for These New AI Stocks. Should Investors Follow Suit?
Philippe Laffont was busy buying Taiwan Semiconductor Manufacturing Company and ASML Holding stock in the first three months of the year.
DoubleVerify (DV) Launches AI-Powered Pre-Screen Content Controls on Meta (META) Threads Feed
DoubleVerify Holdings Inc. (NYSE:DV) is one of the cheap AI stocks to buy according to analysts. On May 18, DoubleVerify launched AI-powered pre-screen content controls on Meta’s Threads feed to enhance brand protection for advertisers. This capability allows brands to avoid content they deem unsuitable before impressions are transacted, building upon DV’s existing post-bid brand […]
Everyone is navigating AI security in real time — even Google
We're in the transition period -- all of us.
I tried Amazon’s Bee wearable and am both intrigued and slightly creeped out
Like other AI wearables, Amazon's Bee offers an odd combination of convenience and privacy anxiety.
I was one of the internet’s first influencers. AI just killed the whole category — and created something better
AI didn't just commoditize content — it made credibility the scarcest resource on the internet. What comes next will reward experts, not entertainers.
Ferrari is using IBM’s AI to create F1 superfans
IBM and Scuderia Ferrari HP take TechCrunch inside how they are redefining the fan experience.
OCR, granite-docling-258m vs granite-docling-2stage-258m: has anyone actually noticed any improvements?
IBM's granite-docling-2stage-258m granite-docling-2stage-258m Granite Docling 2stage builds upon the Granite Docling, but introduces a key modifications: it builds a dynamic prompt that precomputes layout objects found within a page, making it more robust on out of distribution data. What do you think? submitted by /u/Wise_Stick9613 [link] [comments]
Thermocompute constant time inference [P]
I invented thermocompute! It makes machine learning super fast! submitted by /u/arcco96 [link] [comments]
Salesforce Touts AI Promise over Reality in SaaSpocalypse Fight
Article URL: https://www.bloomberg.com/news/articles/2026-05-22/salesforce-touts-ai-promise-over-reality-in-saaspocalypse-fight Comments URL: https://news.ycombinator.com/item?id=48257522 Points: 2 # Comments: 1
PapersWithCode new features - week 1 [P]
Hi, Niels here from the open-source team at Hugging Face. It's been one week since I launched paperswithcode.co, a revival of the website we all loved. It allows us to keep track of the state-of-the-art (SOTA) across various domains of AI, from agents to computer vision and time-series forecasting. The reception has been great, and I'm excited to extend this over the next few months. This week, I've added the following features: - Support for multiple metrics for a given benchmark: leaderboards now support multiple metrics, see e.g., the Open ASR Leaderboard for automatic speech recognition, which supports both Word Error Rate (WER) and the Inverse Real-Time Factor (RTFx) metrics, or the Object Detection leaderboard, which now also reports frames-per-second (FPS) besides mean average precision (mAP) on COCO. https://preview.redd.it/owlxn0b5u23h1.png?width=2878&format=png&auto=webp&s=1dff2f8feab4f160f77c97ceeb5d90e82382e63c - Support for external papers: We do support submitting p
AI news from 200+ sources
Get Started FreeModels & Gen AI
I made a local-first MCP tutorial repo with node-llama-cpp and a custom agent loop
I just published a repo called MCP from Scratch that teaches the Model Context Protocol by building it step by step in plain Node.js. Most of the repo is about understanding MCP itself, but the later modules may be relevant here: I added a local-first setup using node-llama-cpp, GGUF models, MCP sampling, and a custom plan -> act -> observe agent loop. So the repo goes from: raw JSON-RPC and stdio transport to a working MCP server with tools/resources/prompts to local model integration to an agent loop that uses MCP tools with a local GGUF model There’s also an optional LangChain example, but the main path is intentionally minimal and tries to make the underlying mechanics obvious. Key points: plain Node.js, minimal abstractions designed as a learning repo, not a production SDK uses shared local GGUF models for the later modules built for people who want to understand what MCP tooling is actually doing under the hood Repo: https://github.com/pguso/mcp-from-scratch
AI will "raise human consciousness" and "awaken humanity's consciousness to a new level"?
In my discussions with a person who is very devout to their new age spirituality and related "self-development", I was told that AI will "raise human consciousness" and "awaken humanity's consciousness to a new level". I learned about a platform called Mind Valley(?) where they have AI summits about leveraging AI and creating AI coaches for self-development and coaching (in the self-development/spiritual context). In their definition, accepting spirit and the new age beliefs is being awaken and rises one to a new conscious level. This, by the way, is the sort that believes in manifesting, "The Secret", everything that happens is "for the greater good of all concerned", and everything is made out of love. I come from tech and science and have a reasonable understanding of of LLMs work. I find their claims to be pretty out there, much like my opinion about rest of the new age spirituality belief system to be rather baseless. I have no doubt that it helps many, but it's not for me. I kn
The Memento problem in AI agents
TL;DR: I think a lot of agent failures are not really model failures. Agents are being asked to act from scattered, stale, and incomplete workspace data, so they end up guessing, stopping, or handing the work back to humans. My favorite movie is Memento. The movie revolves around Leonard, a man who suffers from anterograde amnesia and cannot form new memories. Throughout the film, he relies on photos, notes, tattoos, and instructions to understand what happened before, what matters now, and what he should do next. Every time Leonard acts, he is reconstructing the situation from whatever his past self left behind. The notes he creates act as the memory he cannot carry himself. They are how he connects the moment he is in to what happened before. That is increasingly how I think about AI agents. An agent can write, reason, summarize, search, use tools, draft emails, analyze data, and execute steps in a workflow. But every action it takes depends on the context surrounding that actio
Are AI agents actually saving you time or just creating more things to manage?
I've been seeing AI agents everywhere lately. Agents for sales, customer support, lead generation, research, scheduling, content creation—you name it. The demos always look impressive, but I'm curious about real-world experiences. For people actually using AI agents in their business: What tasks are they handling? How much time are they saving? Any unexpected problems? Interested in hearing what is genuinely working beyond the hype. submitted by /u/FounderArcs [link] [comments]
Using large language models [R]
Can LLMs be used to come up with a research topic that's worthwhile? Has anyone had good results in coming up with solid research ideas by chatting with an LLM? Maybe using Claude to review existing work and define the research topic. Thanks! submitted by /u/Lonely-Highlight-447 [link] [comments]
AI agents are quietly generating chaos engineering failures enterprises don’t track yet
There is a category of production incident that engineering teams are not tracking yet — because it doesn't fit any existing postmortem template. The agent initiated an action. The action was technically correct given the agent's context. The context was incomplete. The infrastructure cascaded. And, by the time the incident review happened, three teams were arguing about whether it was an agent failure or an infrastructure failure, because the frameworks for thinking about these two things have never been connected. The scale of this exposure is no longer theoretical. Seventy-nine percent of organizations now have some form of AI agent in production, with 96% planning expansion. Gartner predicts 33% of enterprise software will include agentic AI by 2028, but separately warns that 40% of those projects will be canceled due to poor risk controls. What neither statistic captures is the failure mode happening between those two numbers: Agents that are running, that are not canceled, an
Is NVIDIA still the default best choice for local LLMs in 2026?
submitted by /u/pmv143 [link] [comments]
GPU VRAM only for small models with llama.cpp: is it possible?
I'm still in my learning process and so far I've been able to make satisfying use of my setup (4070 with 12GB VRAM + 32GB RAM and iGPU for my GUI). I've been able to run both Gemma4 26B and Qwen 3.6 35B MoEs up to high quants with large context and have about 40 t/s with both. However, I'd like to try a smaller model, ideally a quant of Qwen3.5-9B, with full VRAM usage and no host memory to slow down things. In theory it should be possible, but even gemma4-e2b with a low quant (Q4_IXS) with small context (8192) ends up using about 3.5 GB of RAM on top of the GPU. I've tried all the command line options I could find with llama-server, but so far...no cigar. What am I doing wrong? submitted by /u/Ps3Dave [link] [comments]
at what point do ai-generated images stop feeling ai-generated?
a few years ago it was easy to spot ai art instantly now some generated images look almost indistinguishable from professional photography or digital art. where do you think the line between real and generated starts to disappear? submitted by /u/salarshah-084 [link] [comments]
Hackers are learning to exploit chatbot ‘personalities’
This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on AI mischief, follow Robert Hart. The Stepback arrives in our subscribers' inboxes at 8AM ET. Opt in for The Stepback here. How it started Hacking the first generation of AI chatbots was a laughably simple affair. You didn't need any technical know-how, backdoor access, or even a basic understanding of what a large language model was. You didn't need to code. To get an AI system that had cost billions to build to abandon its safety instructions, sometimes all you had to do was ask. These attacks, known as jailbreaks, had the quality … Read the full story at The Verge.
Robotics
I simply do not understand how massively expensive AI and robotics are expected to be more cost effective than humans
Can someone help me understand this? I mean, how on earth are these companies who are planning to replace us all with beep boops expecting these unimaginably high expense technologies to be better for their bottom line than just paying us low wage unwashed masses? I mean, some dude (respectfully, I use that term genderlessly) here just posted about min wage in their area being $7.25! You are not getting a robot or AI that costs less annualized. Even adding in annual benefits - that is a steal compared to data centers and complex robots who will be absurdly expensive to fix when they break. I’m a white collar worker with deep knowledge of worker costs, even at the top it’s cheaper than what all of this new buggy crap is going to cost. I’m so confused. What am I missing? Why are the evil overlords not interested in our already too cheap labor? submitted by /u/eniac_usabrl [link] [comments]