This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance. By Claudio Masolo
LiteRT-LM brings native support for Gemma 4 Multi-Token Prediction (MTP) drafters, enabling up to 2.2x faster inference. The framework is expanding beyond Kotlin and C++ adding support for new Swift and a JavaScript APIs. By Sergio De Simone
AI companies are using serif to project humanity. Critics are calling it “tasteslop.”
On June 5, 404 Media reported that attackers had been using Meta’s AI customer support agent to steal Instagram accounts. Their approach was simple: They asked the agent to link the accounts to email addresses that they controlled, and the agent complied. One attacker broke into the dormant Obama White House account and made pro-Iran…
Real-time speech-to-speech translation built for accuracy Discussion | Link
I’m building a company monitoring app that reads Firebase data coming from multiple bus DMS devices and returns KPIs for a Svelte dashboard. Is FastAPI a good backend choice for this, especially for a secure, production-ready, scalable, and maintainable API? If not give me please alternatives . I also need a good FastAPI template or guide to start from, a secure way to connect it with Firebase, and the best way to package the app for both Windows and Android. What I need to use ? submitted by /u/Successful-Life8510 [link] [留言]
It seems raw teleoperation data (RGB + joint states) structurally lacks affordance, contact intent, and embodiment-specific kinematic context. (information that can't be reliably recovered post-hoc once the demonstration is recorded) Most current approaches either filter/clean after collection, or rely on simulation to compensate. But neither seems to close the semantic gap for contact-rich tasks in unstructured environments. Is anyone working on supervision at acquisition time, enriching the stream as it's captured rather than labeling after the fact? And if not, is this a real bottleneck or am I overestimating the problem? submitted by /u/Several-Many9101 [link] [留言]
so anthropic just dropped a blog post calling for a global pause on frontier ai development, warning that models could start recursively self-improving and spiral beyond human control. sounds scary. sounds noble. let's talk about what's actually going on here. anthropic is reportedly eyeing a $1 trillion+ ipo, and they just happen to be the ones calling for everyone to stop building. analysts are already asking whether this is really just about freezing the status quo so they can hold their lead. putting it plainly: a pause helps anthropic keep its position and probably grow market share too. and here's where it gets a bit hypocritacal: over 80% of the code in anthropic's own codebase is now written by claude. they're absolutely running the playbook they want everyone else to put down. but the thing nobody's really talking about is regulatory capture. this is textbook. you become the dominant player, go to governments, say "this technology is dangerous, we need oversight, we're the responsible ones, let us help write the rules." suddenly the regulations that get passed only you can afford to comply with, locking in your architecture, your safety benchmarks, your evaluations. smaller competitors get crushed under compliance costs, open source gets kneecapped, and you get a moat that no vc cheque can cross. they compared it to nuclear arms control which sounds serious until you realise ai training is far easier to hide than a missile silo, so any agreement just punishes the people honest enough to follow it. the safety concerns might be real. but the timing, the ipo, the regulatory push is all hard to look at all that and not raise an eyebrow. submitted by /u/Complete-Sea6655 [link] [留言]
We're opening up Creaibo 2.0 beta applications, and I'd genuinely love to get feedback from this community. What is Creaibo? An AI-powered creative tool for images, video, and content production. We're focused on giving creators a more coherent workflow rather than yet another single-task generator. Cora is our core AI assistant inside the product. Why post here? Because people here actually use these tools seriously and have real opinions. We've been building based on the frustration that AI tools are great at individual tasks but terrible at keeping your creative context together across a project. Curious if that resonates. What we're looking for in beta testers: Anyone actively creating content with AI, whether that's video, images, marketing assets, or anything in between. Especially useful: people willing to tell us what's broken. Apply here: https://www.creaibo.com/survery We also published a new Cora demo this week if you want to see what the tool actually does before applying: https://www.bilibili.com/video/BV1ETEF6VEHu/ Happy to answer questions in the comments. submitted by /u/Objective_Dirt_9799 [link] [留言]
found this buried in the openai dashboard and honestly surprised more people don’t know about it it’s called the data sharing program. go to your api dashboard, hit data controls, toggle on sharing. that’s it. you get free tokens every single day. up to 2.5 million tokens daily on the lighter models like gpt-4o-mini, o3-mini, gpt-4.1-mini. for the heavier models it’s 250k tokens per day. resets daily. the trade is your prompts and outputs can be used by openai to train their models. so don’t use it for client work or anything sensitive but for side projects, learning, experiments… you’re basically getting free api access every day just for flipping a toggle not a trial. not a promo. it’s an ongoing program and it just sits there unclaimed for most people submitted by /u/NewMuffin3926 [link] [留言]
submitted by /u/Successful_Bowl2564 [link] [留言]