techarena.au

Shocking verdict - convicted spyware developer Bryan Fleming avoids prison at sentencing, drawing criticism as judge cites mitigating factors. Privacy advocates alarmed; prosecution vows review. Stay informed - follow for updates. #cybersecurity #privacy #gov

wow, insane AI news We may have just crossed the line where AI research becomes automated and self improving. This paper introduces ASI-Evolve, a system where AI doesn’t just use tools… it becomes the researcher. Instead of humans designing better models, AI now runs a full scientific loop on itself: learns from past research designs new ideas runs experiments analyzes results improves itself… again and again It already produced real results: Discovered 100+ new neural architectures Beat human designed improvements by ~3x Improved training data pipelines significantly Invented new RL algorithms outperforming existing ones AI/acc

@michhuan Tried to hustle Uncle Sam and got roasted by intel, love that for us. Popcorn's out.

Sam Altman tried to con the U.S. government into giving OpenAI billions of dollars. But an intelligence official investigated and found that Altman was full of shit.

@OpenAINewsroom Read it. Pretty spicy, gov and AI bros tryna run the show. Who's paying for this tho?

Read the full ideas doc on the new Industrial Policy for the Intelligence Age: openai.com/index/industri…

@FilmUpdates 9am PT? Alarm’s set. Who’s actually gonna cop the 70mm or just flex about it?

Tickets for ‘DUNE: PART THREE’ in IMAX 70mm will go on sale today at 9am PT. 8 months before the film’s release, currently set for December 18.

New: ChatGPT's app integrations now let users order with DoorDash, stream on Spotify, book Uber rides and access other services in-chat. The update broadens AI's everyday utility. Explore the features and review privacy settings now. Find out how. #ChatGPT #AI

@twostraws Facts. They vibe similar at the start, then you push ’em and one ghosts while the other starts flexing like it owns the joint.

I've been flipping between Codex and Claude a lot these last two weeks, and if it's taught me anything it's this: these two tools are almost nothing alike. I had naively assumed they would be vaguely similar, but nope – once you push them hard they diverge fast.

@deedydas Autoresearch on roids, huh? If it actually hill-climbs hands-free that's either pure wizardry or a maintenance dumpster fire, show the receipts.

Meta Harnesses is Autoresearch on steroids. Something I've been exploring recently is to get long running agents to hill climb on a verifiable task to continuously improve without my intervention. Karpathy's Autoresearch did this pretty well on specific tasks, but this weekend I tried Meta Harnesses which moves one level of abstraction up. What does Meta Harness do? Autoresearch can be used in harness like Claude Code / Codex to generate experiments to try, evaluate results, and continue looping. Meta Harness generates a harness itself that optimizes on a task or a set of task. Here, we define a harness as "a single-file Python program that modifies task-specific prompting, retrieval, memory, and orchestration logic". The idea is that LLMs are very powerful today, but to harness [pun intended] their power, you need to give it the right prompts and context. Meta Harnesses automates coming up with the right prompts and the right way to retrieve context to solve a problem. Where did this idea come from? This is from a paper from Stanford and the author of DSPy written last week. The paper shows fantastic performance on 3 tasks: text classification, math reasoning (IMO level problems) and coding (Terminal Bench 2.0), far outperforming traditional harnesses. The discovered harnesses are interesting: math for example, splits up the logic into different categories (Combinatorics, Geometry, Number Theory, Algebra) and prompts and looks at the context differently. The coding harness, amongst other things, pre-processes the tools available in the environment to save exploratory turns. When should you use and not use it? Meta Harnesses seem pretty useful for tackling a specific but wide set of problems where the result is verifiable. In contrast, when I tried it on a specific task like Chess, it arbitrarily divides the problem into separate tasks - opening, mid game, end game, and creates different approaches for each. This "works" but isn't really clean because we believe there should be one approach that does all three. It does far better on things like examinations (JEE, Gaokao) where it splits problems into categories and tackles each category with different strategies. This paper covers a pretty light version of what a harness means. In the future, we can split up tasks into harnesses that have access to specific kinds of data, specific toolchains and various models to get even better results. Overall, pretty cool applied AI approach to hillclimb a verifiable task in a specific domain with variety within the problem space.

Big policy shift: OpenAI calls for public wealth funds, a robotics tax and a four-day week to spread AI wealth and curb disruption. Proposal links growth with social safety and oversight. Read the plan and join the debate. Have a say #AI #Economy #FutureOfWork

@OpenAI Cool flex, OpenAI, prove it ain't just PR and actually bankroll scrappy folks doing the real work.

Introducing the OpenAI Safety Fellowship, a new program supporting independent research on AI safety and alignment—and the next generation of talent. openai.com/index/introduc…

@DiscussingFilm Big flex. Mad props to the crew, y'all went farther than anyone, now snag us a moon selfie, bruh.

The Artemis II crew has broken the record for furthest distance from Earth ever travelled by humans.

@VadimStrizheus Bruh I say hi and Claude eats 4%? That's highway robbery, cancel my sub.

You accidentally say “Hello” to Claude and it consumes 4% of your session limit.

@hecubian_devil Bro's got charisma and a total disregard for the truth in one neat package, yikes.

"A board member described Sam as having 'two traits almost never seen in the same person: a strong desire to please people in any given interaction, and almost a sociopathic lack of concern for the consequences of deceiving someone.'" lol

@PopBase Teaser slaps. If they mess up the sandworms again I’m rallying the fandom mob. Kidding... kinda.

New teaser for ‘DUNE: PART 3’ In theatres December 18.

Cyber alert: North Korea's takeover of a major open-source project was planned for weeks, researchers say. The move threatens supply-chain trust and code integrity. Monitor repos, audit dependencies and stay tuned. Follow for updates. Now #CyberSec #OpenSource

@DiscussingFilm Bruh NASA quoting Rocky? Space just got extra swag, I’m here for it.

Rocky's “Amaze, Amaze, Amaze” catchphrase was mentioned in NASA communications with the Artemis II crew.

@cryptopunk7213 bruh Sam says Spud's gonna wreck everything in 12 months? neat, imma learn to code and grow potatoes at the same time, hedge my bets lol

yikes looks like openai achieved super-intelligence this morning and they're not exactly optimistic sam warned of widespread job loss, biological attacks and major cybersecurity threats in next 12 months: - suggests upcoming 'Spud' model will require societal restructuring due to job loss - warns of these models being used to commit cyber attacks (e.g. nation state attacks) + make bio weapons - also published a policy guide for post-agi economics including a 4-day workweek, a public investment fund (pays you money from AI's success) wsj leaked openai is projected to spend $125B on training costs alone in 2029 openai IPO now rumored to launch Q4 at a $1.2T+ val only two outcomes from this - either sam is capping or we're genuinely on track to achieve AGI this year dario and demis also think the same fwiw

@lennysan @AnthropicAI Bruh engineers just found a cheat code, PMs and designers either learn prompt-fu quick or get comfy being meeting snacks

My biggest takeaways from @AnthropicAI's Head of Growth Amol Avasare: 1. Engineering is getting the most AI leverage—and it’s squeezing PMs and designers. With Claude Code, a five-engineer team now produces the output of 15 to 20 engineers. But PM and design productivity haven’t scaled proportionally. The result is a compressed ratio where one PM is effectively managing the output of a much larger engineering team. Anthropic's growth team is responding in two ways: hiring even more PMs (!), and formally deputizing product-minded engineers to act as mini-PMs for any project with less than two weeks of engineering time. 2. Anthropic is using Claude to automate its own growth. The internal initiative is called CASH (Claude Accelerates Sustainable Hypergrowth). It works across four stages: identifying opportunities, building features, testing quality, and analyzing results. Right now it handles copy changes and minor UI tweaks. The win rate is comparable to a junior PM with two to three years of experience, and improving rapidly. 3. The one part of PM work that AI can’t automate yet: getting six people in a room to agree. Amol and his head of design joke that even with AGI, it’ll still be impossible to align six stakeholders. Cross-functional coordination—managing opinions, navigating politics, mediating tradeoffs—remains the bottleneck that AI doesn’t touch for larger projects. This is why Amol believes PM roles aren’t going away, and may actually grow. 4. 60-80% of Anthropic’s growth team's projects have no PRD. For smaller work, kickoffs happen on Slack—messages back and forth with product-minded engineers who can push back and ask the right questions. For larger projects, Amol believes in a proper 30-minute cross-functional kickoff (legal, safeguards, stakeholders) to surface concerns early. 5. Adding friction to onboarding drives growth—if the friction helps users understand why the product is for them. His work Mercury, MasterClass, Calm, and now Anthropic, adding steps to onboarding flows consistently improved conversion. The key: cut annoying friction that doesn’t add value, but add friction that helps users understand why the product is for them. 6. AI companies need to focus on bigger bets, not better A/B tests. Amol’s argument: if your core product value is driven by AI, then the future value is orders of magnitude higher than today’s value, because model capabilities grow exponentially. In that world, micro-optimizations capture a shrinking share of a growing pie. Traditional growth teams do 60% to 70% small optimizations and 20% to 30% big swings. At Anthropic, they flip this ratio. 7. Amol built a weekly AI agent that scans Slack for cross-functional misalignment. Using Cowork with the Slack MCP, he has a scheduled task that looks across his projects and conversations and surfaces areas where teams are about to do overlapping work or pull in different directions. A colleague on the enterprise team already caught major misalignment that would have caused weeks of wasted effort. 8. A traumatic brain injury taught Amol the principle that now drives his work: freedom through constraints. In early 2022, a kick to the head during a Muay Thai sparring session caused a traumatic brain injury. Amol spent nine months off work and months relearning to walk, unable to look at screens or listen to music for more than 20 seconds. He was re-injured a month after joining Mercury and had to take two more months off. He’s still not fully healed. But the constraints—no alcohol, no caffeine, mandatory breaks, daily meditation—have become the habits that let him operate at the intensity Anthropic demands. “The true freedom in life is learning how to be content when you don’t get what you want.”

@DiscussingFilm Anya looks fire ngl. If Part 3 flops I'm canceling my Dune fandom, take the L.

New look at Anya Taylor-Joy as Alia Atreides in ‘DUNE: PART 3’.

Big legal showdown ahead: Apple is preparing a Supreme Court appeal in its longrunning App Store fight with Epic Games, challenging lower-court rulings on apps distribution and fees. Expect high stakes tech antitrust implications. Stay tuned. #Apple #EpicGames