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Article URL: https://ctrl-watch.xyz/ Comments URL: https://news.ycombinator.com/item?id=48773509 Points: 1 # Comments: 0

My wife wanted lip filler but wasn't sure how it would actually look on her face. Existing AI tools either changed her identity or produced unrealistic results, so I built Lips Up. Upload a selfie and get a realistic preview of different lip filler styles before booking an appointment. Would love your feedback! Comments URL: https://news.ycombinator.com/item?id=48773458 Points: 1 # Comments: 0

KPMG finds nearly a third of execs struggle to understand costs as companies rethink deployments

Article URL: https://alanbuxton.wordpress.com/2026/07/03/we-cant-ask-ai-it-lies-vs-here-is-my-superpower-prompt/ Comments URL: https://news.ycombinator.com/item?id=48773322 Points: 2 # Comments: 0

Article URL: https://geekyants.com/blog/beyond-ai-prototyping-sso-audit-logs-rbac Comments URL: https://news.ycombinator.com/item?id=48773252 Points: 2 # Comments: 0

Article URL: https://blog.andymasley.com/p/ai-art-as-curation Comments URL: https://news.ycombinator.com/item?id=48773133 Points: 2 # Comments: 0

A new way to help gum disease. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

Takeda has entered a strategic collaboration with Hong Kong-based Insilico Medicine to use AI in early-stage drug discovery across the Japanese pharmaceutical company’s therapeutic areas. The companies did not disclose which therapeutic areas or disease targets will be covered under the collaboration. The agreement gives Takeda access to Insilico’s Pharma.AI platform, which supports biological target […] The post Takeda signs $600M AI drug discovery deal with Insilico appeared first on AI News .

Meta CEO Mark Zuckerberg said AI agents aren't progressing as quickly as he had expected, new report says.

I run GrowthSpree, a B2B SaaS marketing agency, selling into the US and Europe. Six months ago we made a bet that the agency model itself was broken for the AI era, so we tore ours down and rebuilt it. This is what we did and what actually happened. The bet: become the first truly AI-native marketing agency. Not an agency that "uses AI tools" by bolting ChatGPT onto a 2015 workflow, but one where AI is wired into how we find demand, win clients, and run delivery. We rebuilt the operating model,

<!-- SC_OFF --><div class="md"><p>​</p> <p>For open-weight LLMs, how practical is it to study defenses against post-release fine-tuning that weakens refusal or safety behavior?</p> <p>I've been seeing “uncensored” or “heretic” variants of new models appear very quickly after release, which raises a question I’m curious about: is fine-tuning resistance a meaningful safety goal for open-weight releases, or is it too narrow because determined users can always modify weights, switch models, or use o

As the parent of two little girls, I often think about how their childhood is different from mine. The seven-year-old is learning about AI at school. The five-year-old is given internet-based homework every week. And they are both absolutely repulsed by the idea of smoking. That was not the prevailing sentiment when I was young.…

Grill, mow, and stay cool this weekend while saving hundreds at Lowe's 4th of July sale.

Kuaishou has raised about $2 billion from investors for its AI video division, Kling. The article Chinese AI video maker Kling raises $2 billion as it gears up for Hong Kong IPO appeared first on The Decoder .

AI agents will happily create 1000+ line source files and add a 20th parameter to a function call, even if there's a rule file telling them not to. So I built Scopewalker: a local MCP server (open source, runs over stdio, and makes no network calls) that gives agents actual numbers to check against. It gives the agent 8 read-only tools: line counts, cognitive complexity/nesting/parameter counts, an oversized-file/function checker against configurable thresholds, doc coverage, code smell detectio

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Article URL: https://github.com/gfernandf/agent-skills/blob/main/docs/ACTION_PREFLIGHT_FORECAST_QUICKSTART.md Comments URL: https://news.ycombinator.com/item?id=48772302 Points: 1 # Comments: 2

A sea of quantum weirdness. ScienceAlert stories are written, fact-checked, and edited by humans, never generated by AI. Don't miss a story, subscribe here.

Article URL: https://digitvest.com/en Comments URL: https://news.ycombinator.com/item?id=48772198 Points: 1 # Comments: 0

Article URL: https://medium.com/@gianlucabailo/the-day-i-played-hide-and-seek-with-an-ai-7a1ee189b5ff Comments URL: https://news.ycombinator.com/item?id=48771783 Points: 2 # Comments: 1

In "Silo," the characters speak to a mysterious voice known as "the algorithm." But have we already met the voice's owner?

Article URL: https://www.youtube.com/watch?v=I9F_VFfLTmM Comments URL: https://news.ycombinator.com/item?id=48771721 Points: 2 # Comments: 1

<h2> Introduction: The Need for Modern Web/AppSec Training </h2> <p>The cybersecurity landscape is evolving at a breakneck pace, but the tools we use to train the next generation of defenders are stuck in the past. Most web/appsec learning platforms still focus on <strong>basic, textbook vulnerabilities</strong>—XSS popups, simple SQL injection, or trivial IDORs. These labs are like teaching someone to swim in a kiddie pool; they might grasp the concept, but they’re <em>ill-prepared for the open

Article URL: https://github.com/anliberant/obsidian-ai-setup Comments URL: https://news.ycombinator.com/item?id=48771700 Points: 1 # Comments: 0

Hi HN,I am building opplic.com an AI employee that you can hire for each of your client. The idea is simple, if you are an agency and managing 10 clients it becomes hectic to manage all if you are doing alone, you might need to hire a SEO guy but wait, 90k per anuum for a single guy !? Think if you want to hire one for each that's almost a million. Here's where opplic comes into picture, Instead of generating random marketing ideas, Opplic continuously learns each client's website, business, ser

<p>Over the past year, AI has become part of many developers' daily workflow. It can generate code, explain unfamiliar frameworks, review pull requests, and even suggest architectural patterns.</p> <p>But I've noticed that the biggest impact isn't on writing code faster. It's on how we think about software architecture.</p> <p>With AI handling repetitive implementation tasks, it feels like architects and senior engineers are spending more time on system design, scalability, security, integration

I’ve been working on this for just a year, mostly with hand coding. I only started using agents in the last few months. It’s not fully finished yet, but the waitlist is open now. I’m giving 80% off for the first three months to everyone who joins the waitlist. Really hope to see your reviews and hear what you think! Comments URL: https://news.ycombinator.com/item?id=48771562 Points: 1 # Comments: 0

<h2> The trust problem nobody scopes correctly </h2> <p>When companies talk about trust in AI, they almost always mean trust in the model. Is the output accurate? Is it hallucinating? Can we rely on what it says?</p> <p>Those are valid questions but they're the wrong starting point. The trust that actually determines whether AI gets adopted or quietly abandoned inside an organization isn't about the model. It's about the system surrounding it.</p> <h2> The four questions that determine </h2> <p>

I'm a bit annoyed by the feeling that we're kind of stuck when it comes to using LLMs for programming. I use Claude Code and Codex, but I haven't been able to enter flow state like I can when I hand write code. This is kind of ironic to me since AI should be a bicycle for the mind, but right now it feels like a bicycle that just brakes abruptly every couple minutes. I stop, wait, review, prompt again. Is there anyone exploring something fundamentally different than the prompt response loop we ha

Article URL: https://www.bbc.com/news/articles/cgrkd41n2v9o Comments URL: https://news.ycombinator.com/item?id=48771466 Points: 3 # Comments: 1

Comments URL: https://news.ycombinator.com/item?id=48771421 Points: 1 # Comments: 1

Article URL: https://soumitradutta.gt.tc Comments URL: https://news.ycombinator.com/item?id=48771271 Points: 1 # Comments: 0

Article URL: https://www.youtube.com/watch?v=59XdUJRzRxc Comments URL: https://news.ycombinator.com/item?id=48771229 Points: 1 # Comments: 0

Article URL: https://agentrc.ai/ Comments URL: https://news.ycombinator.com/item?id=48771202 Points: 1 # Comments: 0

Article URL: https://alprado.com/blog/i-still-enjoy-building-websites-without-ai/ Comments URL: https://news.ycombinator.com/item?id=48771003 Points: 4 # Comments: 1

I'm a software engineer and have been working on this for a couple of months, for fun, and thought I'd share it. If you try it, let me know, I'd be stoked! I was inspired by a friend who wanted to escape the algorithms and had built a small, private reader for himself. He wasn't sure he'd ever release it, so I built my own. It's yet another self-hosted RSS reader, I know. I've been trying to build things like inline YouTube (with filters to drop Shorts and live streams) and webhooks into the cor

Article URL: https://arxiv.org/abs/2606.22737 Comments URL: https://news.ycombinator.com/item?id=48770893 Points: 4 # Comments: 0

I am trying to setup Mr.Jassy as a Slackbot app. I want Mr. Jassy to be our personal AWS butler. Mr.Jassy has access to AWS resources in read only and can help the team answer questions. The way its setup now is that I run 'claude -p' from inside a lambda and is invoked by slack events. Is this the right approach or is there a better way to do this? I also maintain thread context by resuming a previous session. Comments URL: https://news.ycombinator.com/item?id=48770691 Points: 2 # Comments: 0

Article URL: https://www.fastcompany.com/91566861/how-to-avoid-ai-in-as-many-places-as-possible Comments URL: https://news.ycombinator.com/item?id=48770606 Points: 6 # Comments: 1

arXiv:2607.01235v1 Announce Type: new Abstract: Understanding how Large Language Models (LLMs) make token-level decisions during code generation remains a major challenge for both researchers and practitioners. While recent tools provide insights into model internals or generation outcomes, they often lack decoding-time signals, fine-grained uncertainty measures, and interactive mechanisms for exploring alternative generation paths. We present TokenScope, an interactive interpretability and anal