RoGuard 1.0: Roblox's Open-Source LLM Safety Model

Anthropic just dropped Claude Sonnet 4.5—the AI that aims to ship production-grade apps, not just prototypes. Claude Sonnet 4.5 is pitched as a frontier model delivering state-of-the-art coding performance and the ability to build “production-ready” applications. It will be accessible via the Claude API and the Claude chatbot, with pricing the same as Claude Sonnet 4 ($3 per million input tokens, $15 per million output tokens). Anthropic touts industry-leading benchmarks like SWE-Bench Verified, while acknowledging that real-world reliability matters more than numbers alone. Early demos describe autonomous coding for up to 30 hours, including setting up databases, purchasing domains, and even performing a SOC 2 audit. The release also introduces the Claude Agent SDK and a live-realtime research preview called “Imagine with Claude” for on-the-fly code generation. All of this unfolds in a competitive context where OpenAI’s GPT-5 is raising the bar, and Claude-driven tools power applications from Cursor, Windsurf, and Replit. Taken together, the launch signals a shift toward end-to-end AI-assisted software delivery that must balance performance with governance, security, and trust. It won’t be enough to win on benchmarks alone; enterprises will demand strong alignment, robust prompt-injection defenses, and solid observability before shipping at scale. The rapid cadence of flagship models means leadership is fleeting, making ecosystems and real-world validation more valuable than ever. The fact that major players like Apple and Meta are reportedly using Claude internally underscores demand for enterprise-ready, auditable AI that can augment engineering—not replace it. What AI-powered coding play is your team considering this quarter? #AI #Coding #SoftwareEngineering #AIinProduction Anthropic Apple Meta Cursor Windsurf Replit OpenAI Link to Article: https://lnkd.in/gKRsWKwY

The new ear of browser wars have started. With today’s announcement of OpenAI’s Atlas Agentic AI browser, we are entering an era where agents not humans will perform the mundane tasks of clicking web buttons and completing checkout flows. While it is a nice problem to solve, an agentic browser is the wrong solution. Let me tell you why. The web browser was developed to help give humans a better user experience of browsing the World Wide Web. With interactive buttons and graphics, it turned a command line internet into a beautiful and easy to use internet experience. Now AI agents do not need a visual web browser to work! They can easily connect with APIs and interact with CLIs to get things. Asking AI agents to scan through millions of pixels on web pages built for humans is an overkill and the wrong way to solve the problem.

Keep your eyes on the road… I’ve been getting a lot of questions about the Atlas browser from OpenAI this week. It’s one of several new browsers designed to integrate AI agents directly into the browsing experience, giving them control of how we move through the web. But the browser wasn’t built for AI. I see tools like Atlas as a bridge, not the destination. Eventually, agents will interact directly through contracts and protocols with no need for a browser at all. Innovation is outpacing governance. People see the benefits but overlook the risks. It’s like handing the keys to a ten-year-old. They love the idea of driving, can barely see the road ahead, and have no imagination for how bad this could go. AI agents still hallucinate, carry bias, and remain open to manipulation. Yet people are connecting them to personal and corporate systems that hold sensitive data. We are racing toward a future few understand. Progress will continue, but governance, safeguards, and expertise need to catch up before we find out the hard way who is really driving the car.

Finally, the secret is out. The best image editing model in the world is not Google’s Nano Banana, or OpenAI’s, it is Riverflow 1, built by our team here at Sourceful. Independent testing by Artificial Analysis ranked Riverflow 1 as the #1 AI model for design-grade image editing in the world. After ten days of speculation on X and Discord about the mysterious state of the art Riverflow model, we are happy to share Riverflow 1 is ready for action. Riverflow 1 is now live inside Sourceful, and available to developers through Runware's API starting tomorrow. Sourceful, Google, Alibaba, Bytedance... it's a great start! We named it Riverflow because no matter what, a river will find a way to its target. 🎯 What you need to know: 1️⃣ Number 1 Image Editing according to over 2,300 user votes. 2️⃣ Excels in text editing, precise control, background changes, style transfer and for the first time in an image editing model, producing transparent backgrounds. 3️⃣ 11 aspect ratios supported. 4️⃣ Comes in 3 strength variants (mini, normal and pro). 👉 Learn more: https://lnkd.in/ejhpffAm

OpenAI just launched Atlas, it's AI powered browser. Have been using Comet since early launch days. Never felt like moving back. AI-powered browsers seems like the future of browsing and productivity. They have lot more context than just GPT and can see almost everything that you do on internet. I also love the ease at which you can ask question about a page or ask the agent to do something for you. Initial Review of Atlas : Atlas Agent seems to be hallucinating, doing something very random as asked or shared. Comet does a far greater job. Asked it to research a topic related to work. Went off to Canva for some reason and trying to do something there. Though search works well and is able to get good context from the screen. Would still prefer Comet, though far better than Dia (Arc).

⚙️ Tomorrow might change how we build with AI. 🧠 Sam Altman just announced we should expect "new stuff to help you build with AI" by tomorrow. I think it might be Agent Builder — a native, no-code environment to design and deploy autonomous AI workflows. For the past months, builders have been hacking together stacks like Zapier, n8n, Make, and Claude Workflows to simulate agent behavior. It worked — but it always felt fragile. One tweak in an API or an auth key, and everything stops working. ⚡ Now imagine the same power, inside OpenAI itself — where you drag logic blocks, connect tools, and publish production-ready agents without touching an API key. Before: 10 browser tabs, 5 plugins, and prayers it doesn’t break. After: One canvas. One click. Full autonomy. If this is what’s coming, it’s AI’s App Store moment — when building intelligence becomes as accessible as building a website. 🚀 Tomorrow might be the day AI stops being a tool for developers… and becomes infrastructure for everyone. 💬 What are you hoping OpenAI announces tomorrow?

⚙️ Excited about OpenAI's tease from Sam Altman on new AI building tools dropping tomorrow—it's got the community buzzing, and posts like this one capture that hype perfectly. But let's add a mild critique: while an "Agent Builder" sounds like a game-changer for no-code workflows (bye-bye fragile hacks with Zapier and n8n!), it feels a bit incremental. We're streamlining developer tools, sure, but is this truly the "AI's App Store moment" or just another layer on existing infrastructure? What I'd love to see are a few bold iterations beyond agents: starting with enhanced reasoning models that chain thoughts more fluidly, then augmentation layers that integrate human-AI collaboration seamlessly. From there, we could evolve into systems that build pathways into deeper, layered knowledge ecosystems—think interconnected webs of data and insights that self-evolve. And ultimately? Models capable of generating intelligent life forms, sparking entirely new paradigms of creation and simulation. If tomorrow's announcement pushes us even a step closer to that trajectory, it'll be huge. 🚀 What's your take—what wild evolution do you hope OpenAI unveils next? #AI #OpenAI #Innovation

https://lnkd.in/gqwku6kK OpenAI Eyes $500M Gaming Data Startup to Boost AI Capabilities OpenAI is reportedly in talks to acquire a videogame data startup for around $500 million, signaling its intent to enhance AI training with interactive and dynamic datasets. The unnamed startup compiles extensive player behavior, physics simulations, and gameplay interaction data from millions of sessions, offering deep insights into human decision-making and creativity—key ingredients for next-generation multimodal AI models.  #OpenAI #AI #GamingData #TechNews #Innovation #ArtificialIntelligence

Modern AI stacks are evolving faster than the models they run on. Teams are now mixing OpenAI, Anthropic, and open-source models, sometimes even running them locally for privacy, latency, or cost reasons. But migrating between models shouldn’t mean rebuilding your entire app. In our latest post, we share how to use Fireworks Eval Protocol with Ollama to keep your evaluation workflow intact while swapping model backends effortlessly. The setup lets you compare OpenAI and OSS models head-to-head using the same evaluation harness, so your results stay consistent, and your code stays clean. We walk through two examples: agent evaluation on the Chinook dataset and LLM-judge scoring from Langfuse traces. One surprising result: qwen3:8b outperformed gpt-4o-mini, making it a strong option for local deployment. If you’re thinking about migrating to open models without losing rigor or observability, this one’s worth a read: https://lnkd.in/gU-JHMw9

OpenAI's Sora launch has been a viral sensation, but a platform overflowing with Pikachu videos, Michael Jackson deepfakes, and celebrity likenesses probably wasn't what the legal team had in mind. Welcome to AI News in a Minute, brought to you by Tavus, the future of interactive video. I'm Jerome W Dewald. This is Monday, October 6, 2025. OpenAI Sora changes are front and center: Sam Altman announced opt-in controls and revenue sharing to rein in a Wild West of UGC and deepfakes. Sora hit number one in Apple's App Store in twenty four hours, pushing copyright and creator-economics into the spotlight. Meanwhile, OpenAI's ambitious screen-free device with Jony Ive is hitting design and compute bottlenecks that could push launch past 2026 — a reminder that hardware is a different beast. On the research side, Google’s PASTA is learning user image preferences and beating standard models eighty five percent of the time, while Tencent’s HunyuanImage 3.0 just topped LM Arena, proving open-source can outpace closed systems. Visuals: show Sora clips, Altman blog, device sketches, PASTA choices, and Hunyuan images. Bottom line: platforms are being forced to govern likenesses, hardware is harder than code, and personalization is the new frontier for creative AI. That was your AI News in a Minute with Jerome W Dewald. Stay ahead in the AI race! Leave your thoughts about Sora platform future in the comments, give this video a like, and hit subscribe so you don't miss tomorrow's AI News in a Minute!