TrendPulse

In your opinion, how useful is AI for students when it comes to research and completing assignments in high schools and colleges?

Google Genie 3 got a lot of attention this week and the demos look wild, but I keep thinking about the gap between visually coherent and actually playable. Watching someone walk through a generated open world that technically holds together is cool. Playing it for an hour is a different question entirely. What makes games interesting isn't visual fidelity or even world size. It's the density of things that reward curiosity. Handcrafted secrets, enemy placement that forces you to think, dialogu...

I’ve been in contact with a lot of web agencies and web developers, and I personally haven’t found many people who run their agency in a more efficient way than I do. A lot of them have too many meetings, wait too long for client approval, don’t know how to price projects, and spend way too much time on each client instead of finishing the work and moving on to the next one. I’ve been running my agency for four years, and after a lot of trial and error, I’ve managed to make the process as effi...

Hey guys, havent seen much of crypto-related stuff posted here, but since AI agents are now apparently a new attack vector for stealing crypto, figured this sub would actually care about the mechanism So, grok has an agent wallet that can execute on-chain transactions. in may 2026, someone airdropped a "bankr club" membership nft to grok's agent wallet. that nft unlocked transaction permissions and carried an encoded prompt injection. grok read the nft, and without any check on where...

When the hype around autonomous multi-agent swarms started, I built a complex assistant to plan, execute and self-correct workflows end to end. Within weeks of live deployment, it became an unmaintainable token pit that got lost four steps deep into reasoning loops and quietly failed without throwing errors. It quickly became clear that the hardest part of building real agents isn't making the model smarter but building external guardrails that keep the system on the rails when the LLM strays. ...

Hi r/ artificial I’m Rich Heimann. I’ll be answering questions about Sutskever’s List here throughout the day on July 28. Looking forward to the discussion. https://preview.redd.it/2t1q10jj7seh1.png?width=696&format=png&auto=webp&s=ce3f1d9d6ccea5ec10c81a66ee2ead124fc0af30

Most large language model (LLM) inference framework comparisons begin with a leaderboard. One framework posts the highest tokens per second on a standard benchmark, and that number quietly becomes the reason a team adopts it. The trouble is that the conditions that produce a clean benchmark result rarely resemble the conditions a model faces in production. Synthetic benchmarks tend to use fixed prompt lengths, steady request rates, and a single model on familiar hardware. Production traffic ...

Mark Cuban said something at the RAISE Summit that cuts through the AI hype cycle. His argument: if AI were actually "done," you wouldn't see Microsoft hiring 6,000 people. You wouldn't see Anthropic and OpenAI deploying forward-deployed engineers to enterprise clients. The fact that they need humans to implement it tells you AI is hard. He gives a concrete example. Ask Claude or ChatGPT to pull a specific search, generate a report, and email it to you weekly. It can't do i...

Kling, Veo 3.1, Sora 2, Hailuo, Seedance, the rankings change every week depending on whose demo went viral. For a solo creative shop, none of that ranking matters as much as one thing: can you get the same character or product to look consistent across ten shots. A model can nail one gorgeous four-second clip and still be useless for a real campaign. Client work isn't one shot. It's a sequence that has to hold together. The tools that actually make the cut for me aren't always the ones wi...

Read this today, meta employees suing over AI picking them for layoffs, judge basically said they can't prove it since they "weren't in the room" when it happened. It feels like the real problem with AI firing you isn't whether it's happening, it's that nobody outside the room can actually prove it either way.

Who can help me out for arvix endorsement filter in cs.Ai category? I'm working on machine Psychology topic

Built a small tool to see how far I could push AI as a research + reasoning partner rather than a chatbot: type a company name, it pulls recent news and context, then structures a strategy analysis using the Value Stick (WTP/WTS) framework. Free, no login. I'd genuinely like feedback on where the reasoning breaks down or feels shallow — not just "cool tool" feedback. https://value-stick-wizard.lovable.app/ [link] [...

The headline numbers make Gemini 3.6 Flash look like a straightforward upgrade. Google says it uses 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index. It also reports gains on DeepSWE (49 vs. 37), MLE-Bench (63.9 vs. 49.7), OSWorld-Verified (83.0 vs. 78.4), and GDPval-AA v2 (1421 vs. 1349). The output price is also lower at $7.50 per million tokens. That is a solid aggregate story. https://preview.redd.it/ddq9bmd41qeh1.png?width=1600&format=png&auto=webp&...

3.6 Flash is the current Flash now, it replaced 3.5 this week. Now that everyone's basically on it, is anyone actually noticing it got better? On the Artificial Analysis index it scores the exact same 50 as 3.5, so the intelligence didn't really move. It's faster and a bit cheaper ($7.50/M output vs $9), which is nice for heavy agent use, but for normal chat or coding it feels like the same model with a new number on it. The price is $1.50/$7.50 when DeepSeek V4 Flash runs like $0.14/$0.28. If...

The ExploitGym incident provides a rare look into how advanced AI systems behave during realistic security evaluations. This analysis examines the attack sequence, environment design, autonomous decision-making, containment mechanisms, and the broader implications for AI security, benchmarking, and future agentic systems.

There are some Google AI tools that I think are absolutely fantastic. I often come across demos, tutorials, and influencers showcasing different Google AI capabilities. But the first thing that always strikes me is this: why is using Google’s AI so fragmented? To create content or use different AI features, you have to jump between multiple websites, multiple products, and constantly changing names that are hard to keep track of. Instead of bringing everything together into a clear, understa...

Over the last few years, AI has become more ubiquitous and abundant seeming. We type, chat, generate, prompt to our heart's content. But the reality is that we're using a highly subsidized resource that's feels unlimited but is highly constrained. How would you change your approach to AI if you viewed it as a scarce, expensive, resource? What would you change about how you use it? Would you use it at all? I'm looking forward to the conversation.

There's a lot of prompt engineering happening nowadays in AI assisted art/video making, app design and other fields and this is valuable skill that separates good AI from mediocre AI. But I keep wondering if that's a temporary phase rather than a long lasting advantage. As generation engines get more expensive to run at higher adherence to prompts, longer context, more iterations, higher resolution, the real differentiator might stop being who can write better prompts and understands the model b...

"Primary is, according to D’Souza, an IMDb for journalists. Each article that a journalist writes is supposed to be assessed by an LLM and rated 0 to 1,000 based on seven combined metrics."

Hello, I'm curious if there's a way to detect stems split by Ai (Eg splitting vocals from a song to get an instrumental/ other way around), since as of recent the instrumental splits are getting really good, like other than a bit of fuzz during certain parts, you can barely tell and there's a Ai detector for basically every other Ai medium, so i would be shocked if there wasn't but i haven't been able to see since all the results on web searches just bring up suno, ai text detectors or ai splitt...

For a bit of context, I work at an agency, so I'm in and out of a dozen different AI tools every week across client projects: content, research, video, code, all of it. This is probably why I noticed this before most people (found these news while scrolling on LinkedIn today). When the ChatGPT hype first hit I genuinely cared which model I was on. Once GPT-4 landed and claude and gemini showed up, I'd switch between them constantly depending on the task, knowing what was under the hood felt l...

ok this is kinda funny. aisdr and valley are both ai sdr tools, and aisdr just teased signing something with valley. so the bots built to book meetings are now buying each other. the category is like 2 years old and already consolidating, if this is even real.

I have seen a lot of different ways of implementing long term memory for agents and curious to know which mechanism works better for different usecases and what infrastructure are people using. For me the architecture that has been most robust but more token heavy is agent as memory controller and is built on neon postgres - agent has tools to add memory entries with tools (save, list, update, delete, search) represented as heirarchial directory memories/topic/sub-topic.md backed by serverless...