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New to agents, mcp , etc how do I get to a point where i can lay back and let my agents do the work
Currently working on some projects. I have some agents and chrome scrap tasks id like it to do. Does Aider need permission for certain commands or is there a safety guardrail? Is Aider the best, I think I am done with Antigravity with Gemini models for coding it is trash. submitted by /u/Lazyrecipe5264 [link] [comments]
I tracked 47 new agent products launched in 2026. Here are 5 ways they differ from the last generation (chart inside)
I made a local-first MCP tutorial repo with node-llama-cpp and a custom agent loop
General AI
Anyone using an AI workforce for lead gen that brings in real conversations?
been looking at this whole AI workforce thing for lead gen and honestly I can’t tell what’s actually useful vs just another outreach tool with better branding. I’m not trying to send a bunch of random messages. I’m more interested in agents that can find decent prospects, do a bit of research, draft messages that don’t sound copy pasted, follow up at the right time, and keep track of who’s actually worth talking to. I’m fine with reviewing/iterating the system during the initial setup but if I have to manage every small step then it kinda defeats the point. anyone using an AI workforce or agent setup for lead gen in a way that gets finds qualified leads? submitted by /u/IllustriousLength991 [link] [comments]
I spent 10 years and $13M+ running ads for major brands. I want to help 3–4 small businesses launch — for free
Quick context so this doesn't read like every other "free website" post: I'm not a bootcamp grad padding a portfolio. I spent the last decade in digital marketing, managing over $13M in ad spend for established brands. I recently went out on my own and I'm building a small set of real case studies — businesses I actually helped get off the ground. The honest reason it's free: I want a few genuine results I can point to, and I'd rather earn them by helping real people than by running fake demos. Here's the thing about 2026 — building a website or app isn't the hard part anymore. AI can generate one in an afternoon. The hard part is knowing what to build, who it's for, and how to actually get paying customers through the door. That's the gap I want to close for you. What I'll do, end to end: A real website, web app, or simple automation built for production — something you own the code to, not a throwaway template Ad setup that doesn't bleak money — Google and Meta, structured pro
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.
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
Nvidia Quietly Builds Major AI Portfolio Shaping Investor Risk And Optionality
Nvidia (NasdaqGS:NVDA) has built one of Silicon Valley's largest private AI investment portfolios under CEO Jensen Huang. The company nearly doubled its private company holdings over the past year, according to its latest quarterly disclosure. Nvidia deployed record capital into emerging AI and technology ventures, including nearly US$18b into private ventures in a single quarter. As of 26 April, Nvidia reported more than US$42b in private company holdings linked to the broader AI...
Nvidia's Jensen Huang Just Delivered Big News to Shareholders. And It May Influence Your Decision on Whether to Buy Nvidia Stock Right Now
During Nvidia's earnings report, Huang talked about the next chapter of the AI story.
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.
We made a map of the doom debate
This was produced as a part of the AI Safety Camp 2026 "Assumptions of the Doom Debate" project, led by Sean Herrington, who was also the lead author on this post. The other participants have equal contributions and are listed in no particular order. It is the first in a sequence we intend to publish over the coming weeks. TL;DR: We have created a breakdown of AI threat pathways, which can be accessed at https://lifeuniversesafety.com/doom-assumptions/index.html This breakdown is in a tree format, and we allow people to set their own probabilities for each threat pathway You can use this to drill down into components of your P(Doom) You can analyse the sensitivity of your beliefs to changes in your assumptions You can compare your worldview to others’ and find cruxes automatically The exercise of creating this sort of structure is valuable as a way to think about the future in a more general manner. Introduction Just about everyone in the AI community seems to disagree about the ris
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.
Elon Musk has given up on solar power (on Earth)
Elon Muks's xAI has gone all in on natural gas, while SpaceX is obsessed with orbital data centers. What happened to the "solar-electric economy" he promised?
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]
AI news from 200+ sources
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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
My pipeline for the best speech to transcript results
I wished the new ASR (automatic speech recognition) models to give me the accurate output but I was disappointed, specially when the input was multilingual and noisy (all my use cases). I had to put in significant efforts in audio pre/post processing and some additional tools in the pipeline. This is how my pipeline works in the end: I choose my ASR model depending on my use case. Sometimes it is a local model (e.g. Qwen 3 ASR works well) and sometimes it is a hosted online model (whisper or voxtral or gpt-4o-transcribe or google/chirp). I prepare the audio for the best outcome e.g. denoising, chunking on pauses, matching the sample rate of the ASR model, etc. Send the processed audio to the chosen ASR models (or bootstrap it locally using hugginface pipeline). Enrich the output transcript with timestamp and speaker info using diarizarion models (e.g. pyannote) Use LLM to fix any mistakes in the transcript Even then my transcript is not 100% accurate all the time but this is
I was messing with agentic organizational strategies and came up with an automated starfish that solves social problems
Not a promotion because it's not for sale 😎 submitted by /u/Kootlefoosh [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
Google’s new anything-to-anything AI model is wild
Just a stuffed deer having the time of his life. | Image: Gemini / The Verge Last year I deepfaked my kid's stuffed animal to make it look like his plush deer was on vacation. It was an experiment to see if I could re-create the events depicted in a Gemini ad Google was running, and I never showed the videos of Buddy the deer on his adventures to my four-year-old. But it was a revealing exercise that made me think a lot about the difference between some harmless fun with generative AI and full-on slop. Maybe that Venn diagram is a perfect circle! Maybe not. But what I know for sure is that the tools to make realistic videos are surprisingly good, requiring surprisingly little effort and know-how. And that trend is c … Read the full story at The Verge.
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.
AgenticROS Now Supports NVIDIA NemoClaw!
Excited to share that AgenticROS now supports NVIDIA NemoClaw as a first-class Physical AI agent platform for ROS-powered robots! NemoClaw packages OpenClaw inside a policy-enforced OpenShell sandbox with managed inference. AgenticROS extends that environment into the physical world by connecting the sandboxed agent to ROS2, RealSense, and robot control interfaces. With the new NemoClaw integration, an agent can: - Use ROS 2 tools for topics, services, actions, parameters, camera snapshots, and depth sensing - Connect from the NemoClaw sandbox to host-side ROS / RealSense / rosbridge over a controlled network policy - Access robot perception and actuation while keeping the AI runtime sandboxed - Run AgenticROS as an OpenClaw plugin inside NemoClaw - Support real robot behaviors through the AgenticROS skill architecture The recommended setup keeps ROS 2 and RealSense on the host, where hardware drivers already work well, while NemoClaw runs the agent and AgenticROS plugin in
Qwen3.6-35B-A3B vs Gemma4-26B-A4B
Just wondering how are people's experience with both these models! I've had some nice results with Qwen but Gemma4 runs so much faster here. I'm using a Radeon 9070 XT and always latest llama.cpp. submitted by /u/MarcCDB [link] [comments]
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]
I built 10 gamified, interactive presentation decks to teach Agentic AI (Stop falling asleep reading whitepapers)
Hey everyone, I've noticed a massive gap in how developers are trying to learn Agentic AI right now. There are hundreds of theoretical whitepapers and boring PowerPoint decks about ReAct loops, GraphRAG, and Semantic Routing. The problem is passive reading. You read a 20-page doc on multi-agent handoffs, close the tab, and immediately forget how the architecture actually works. So, I built a custom presentation engine directly into the AgentSwarms platform and just published 10 gamified, interactive slide decks. Here is how the learning loop works: Instead of just staring at static diagrams, the slides require you to interact with the concepts. You click to reveal logic paths, test your intuition on how an agent would route a specific prompt, and actively engage with the architecture. It uses active recall so the patterns actually stick in your brain before you ever touch a line of code. The decks cover everything from zero-to-production: The Basics: What a system prompt actual
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]