Still facing copyright lawsuits, AI music generator Suno raises another $400M
The prominent AI music generation startup is now valued at over $5.4 billion -- about seven months ago, it raised at a $2.45 billion valuation.
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The prominent AI music generation startup is now valued at over $5.4 billion -- about seven months ago, it raised at a $2.45 billion valuation.
PlayStation used its most recent State of Play showcase to make it clear where its focus is. After a series of costly live-service stumbles, it's getting back to focusing on premium, narrative-driven, single-player games. That statement was made clear with how it started and ended the hourlong show. The showcase began with an extended look […]
The startup's own stack for Africa and Middle East is now handling more than 17,000 calls per day.
The company is reducing its workforce as it exits 22 countries, reduces management layers, and invests in its infrastructure to scale its platform.
U.K. regulators are requiring Google offer a tool allowing website publishers to opt-out of generative AI search features. The option will be tested in the U.K. then rolled out globally.
At Microsoft's annual Build conference on Tuesday, the company announced a slew of new or expanded AI initiatives, including a super app, in-house reasoning models, a cybersecurity tool, and OpenClaw-esque AI agents. All this news added up to a clear message: Microsoft is positioned to be one of the biggest players in AI, and it's […]
This open-source community project lets you create a StumbleUpon-like experience for recommending your favorite sites.
WhatsApp will charge businesses for using its AI agent based on token usage
Doubts linger over whether Meta can close the gap with rivals.
Making sense of what you get from Claude AI at the free tier, especially as limits are vague and keep shifting.
The Series F round values Coralogix at $1.6 billion and comes less than a year after its previous raise.
Plex has come a long way from being just a personal media server. Over the past few years, it has transformed into a streaming hub, today featuring ad-supported content and movie rental options. Now, the company is setting its sights on competing with social networking platforms like Reddit and Letterboxd: on Wednesday, Plex unveiled several […]
Hi — I'm E Lion (Eric), Hawaii-based builder at Coral Crown Solutions . I ship production code on my own domains—not tutorials: elionmusic.com — 400+ promo pages, vinyl-style player UX, Vapi phone agent + OpenAI "Shine" chat (one knowledge base, unified CSV log, webhook follow-up emails) prayerauthority.com — faith-tech at scale; WebM flying angels , SOAP journal, oracle tools Digital Zion — Three.js metaverse + native 3D desk fork + localhost bridge APIs Stack: PHP 8, vanilla JS, webhooks, JSON-LD / Search Console, ElevenLabs, Playwright, Electron (Shine assistant), Cursor pair-programming. Looking for: peers who respect hard integration work (SMTP, CORS, cPanel, webhook auth) and clients who need a real AI front desk or artist/ministry platform. Live demos: coralcrownsolutions.com · elionmusic.com Happy to give honest feedback on your builds—drop a link.
What is an LLM evaluation harness? A deep dive into lm-eval-harness You fine-tuned a 7B model. It aced your smoke tests, your colleague ran a few prompts and shrugged approvingly, and the README is now full of cherry-picked outputs that look great in a screenshot. Then someone asks: how good is it, really? — and you realize you have no number to point at. No MMLU score. No HellaSwag. Nothing reproducible, nothing you can defend in a PR review, nothing you can compare to last week's checkpoint. That's the gap an evaluation harness fills. It turns "vibes-based evaluation" into something with a score, a stderr, and a config file you can re-run next Tuesday. Why evaluate LLMs at all? Two reasons that actually matter: Comparability. If you can't put a number on a model, you can't compare it to anything else — not the previous checkpoint, not the open-source baseline, not the commercial API you're trying to replace. Leaderboards are noisy and gaming-prone, but a local leaderboard with the tasks you care about is one of the most useful artifacts a team can build. Regression detection. Most model regressions are silent. A 0.3-point drop on MMLU won't show up in a chat session, but it will show up in CI. People who ship models for a living treat evals the way backend engineers treat unit tests: mandatory, run on every PR, and blocking on regressions. You don't need a hundred benchmarks. You need the three to five tasks that map to your actual use case , plus one or two general capability anchors (MMLU, HellaSwag) so you can sanity-check that you didn't accidentally destroy basic reasoning while you were tuning for your domain. What is an "evaluation harness"? An evaluation harness is the software that sits between a model and a benchmark. It handles the boring-but-critical parts: loading the model weights, tokenizing prompts in the way the benchmark expects, running inference, extracting the answer from a longer generation, scoring it against a ground-truth key, aggregating
Swap debugging war stories\n\nI have been living in webhook + PHP + email land (Vapi, OpenAI, PHPMailer, CSV logs).\n\nDrop your stack in a comment (even one line). I will reply with the first three places I would look for a silent production failure.\n\nNo sales pitch — trying to meet dev friends who ship unglamorous integration work.\n\nMy builds: elionmusic.com · prayerauthority.com
Amazon's Stargate series greenlit last year has been cancelled.
Sepehr Khosravi discusses the evolution of developer productivity tools. Evaluating the strengths of tools like Cursor and Claude Code, he explains actionable techniques for senior engineers - including context engineering, custom rules, and Model Context Protocol (MCP) integrations. He shares real-world benchmarks and strategic frameworks for balancing AI adoption with clean code quality. By Sepehr Khosravi
Researchers are using machine learning algorithms to decrypt historical pencil-and-paper ciphers.
OpenAI outlines a blueprint for U.S. governance of frontier AI, proposing a federal framework for safety, resilience, and national security.
OpenAI outlines its public policy agenda for AI, including safety, youth protection, workforce transition, and global standards to ensure AI benefits society.