183112724
submission
ZipNada writes:
When Anthropic introduced its powerful new model, Claude Mythos, this spring, companies and countries freaked out. The general-purpose model, its creators claimed, could discover software vulnerabilities that no one knew existed.
Rather than release Mythos to the world, the company gave it to cybersecurity experts at major companies that build or maintain critical software infrastructure and told them to use it to find and fix bugs before Anthropic unleashed it on the world.
But less than two weeks later, 22-year-old developer Kye Gomez made educated guesses about the core design that makes Claude Mythos so powerful and published OpenMythos, a public project that approximates Anthropic’s breakthrough. Gomez’s code raced through the research community like a prairie fire.
This story has several startling implications: if a self-taught developer can reverse-engineer the structural innovation of a multi-billion-dollar lab in a matter of days, then the proprietary moat around AI architecture may already be gone.
183093904
submission
ZipNada writes:
Given the dour headlines as of late concerning the diminishing amounts of entry-level software development jobs, coupled with predictions of applications entirely AI-generated, one could be forgiven for assuming that software developers may soon be an endangered species. However, the data tells a different story.
James Bessen, professor at Boston University, has been pushing back for some time against the talk of AI and automation displacing jobs on a mass scale, and lately has been arguing that the roles of software developers are nowhere near extinction.
Software developer jobs have continued to grow
AI is certainly not killing the software developer, Bessen said in a recent analysis. AI is taking over software development tasks and boosting productivity and output, but that is not translating into lost jobs, he argued. Instead, the types of software skills sought by companies are changing.
"Surprisingly, however, after three years of AI use, software developer jobs have continued to grow robustly, reaching record levels of employment — 2.5 million in February," Bessen said in the report, citing data from the US Bureau of Labor Statistics. The number of software developers in the US has grown by over 400,000, or 19%, since ChatGPT was introduced in 2022. At that time, the employed software developer population was just under 2.1 million.
181740140
submission
ZipNada writes:
The energy company Vattenfall and the tech company Spoor have analysed the extent to which wind turbines endanger birds at the offshore wind farm in Aberdeen. Over a period of 19 months — from June 2023 to December 2024 — video recordings of a wind turbine were made with the help of AI-supported analyses. A total of 2,007 bird flight paths near the monitored turbine were examined.
"By combining AI-powered detection and detailed expert analysis, we can replace assumptions with concrete observations and measure actual behaviour in the immediate vicinity of wind turbines," says Ask Helseth, Chief Executive Officer and co-founder of Spoor.
The study found that there was not a single collision
A study by the German Offshore Wind Energy Association (BWO) also shows that migratory birds almost completely avoid wind turbines.
For one and a half years, researchers analysed over four million bird movements with the help of radar and AI-based cameras. The result showed that over 99.8 per cent of migratory birds reliably avoided the wind turbines.
181200044
submission
ZipNada writes:
Two software researchers recently demonstrated how modern AI tools can reproduce entire open-source projects, creating proprietary versions that appear both functional and legally distinct. The partly-satirical demonstration shows how quickly artificial intelligence can blur long-standing boundaries between coding innovation, copyright law, and the open-source principles that underpin much of the modern internet.
In their presentation, Dylan Ayrey, founder of Truffle Security, and Mike Nolan, a software architect with the UN Development Programme, introduced a tool they call malus.sh. For a small fee, the service can "recreate any open-source project," generating what its website describes as "legally distinct code with corporate-friendly licensing. No attribution. No copyleft. No problems."
181199794
submission
ZipNada writes:
In a move that feels less like a corporate transaction and more like the final punchline to a 40-year industry rivalry, AMD announced Wednesday that it has agreed to acquire Intel, the company it has spent decades chasing, imitating, undercutting, suing, licensing from, and lately outperforming.
The all-stock transaction, which AMD described as a "once-in-a-generation opportunity to unify x86 innovation," would combine the two companies under a single umbrella just a few years after such an outcome would have sounded ridiculous.
For most of modern computing history, Intel was the empire and AMD the scrappy survivor, the perpetual second source that somehow kept finding ways to stay alive. Now, after a bruising run of manufacturing delays, product stumbles, strategic resets, and a historic reversal in investor confidence, Intel is poised to be absorbed by the smaller company it long treated as a footnote.
181166806
submission
ZipNada writes:
Every co-founder Elon Musk recruited to build xAI has now reportedly left the company. Manuel Kroiss, who led the pretraining team, told people this month that he was departing. Ross Nordeen, described by Business Insider as Musk’s “right-hand operator,” left on Friday. They were the last two of eleven co-founders, all of whom have exited a company that was valued at $250 billion when SpaceX acquired it in February and that Musk himself described two weeks ago as having been “not built right the first time around.”
The departures are not ordinary startup attrition. The researchers Musk assembled in 2023 were among the most accomplished in artificial intelligence. Jimmy Ba co-authored the 2014 Adam optimisation paper, the most-cited paper in AI with more than 95,000 citations. Igor Babuschkin, the chief engineer, came from Google DeepMind. Christian Szegedy came from Google. Tony Wu led the reasoning team. Greg Yang, Toby Pohlen, Zihang Dai, Guodong Zhang, and Kyle Kosic brought experience from DeepMind, Google, Microsoft, and OpenAI. That entire cohort is now gone, and the company they helped build is being, in Musk’s words, “rebuilt from the foundations up.”
180999726
submission
ZipNada writes:
Over the weekend, the OpenAI cofounder and former director of AI at Tesla posted a graphic showing how susceptible every occupation is to Al and automation, using Bureau of Labor Statistics data. Different jobs received scores on a scale of 0 to 10, with 10 being most exposed.
While the overall weighted exposure was 4.9, Karpathy’s data also showed that professions earning more than $100,000 a year had the worst average score (6.7), while the those earning less than $35,000 had the lowest exposure (3.4).
180839462
submission
ZipNada writes:
Gopal said that arguably, many businesses exist that AI can never be trained on, “because this is real-life business that moves.” Real people who have conversations and continually update a business context will always be one step ahead of the machines, he explained. “Are you going to retrain for that one individual conversation for one day?” he asked, and then retrain on a rolling basis every time your business context changes?
Gopal was bearish about how much this context can be captured, estimating that 70% of the effort required to make AI useful relies entirely on unwritten business context that exists only in human heads. “You fundamentally cannot train a system” on this fluid daily reality, Gopal explained, noting that real-life business constantly changes based on individual conversations and human interactions. While AI can automate tasks at the absolute top (coding) and the absolute bottom (physical robotics), the vast middle ground of knowledge work requires human context.
180771790
submission
ZipNada writes:
Let me give you an example so you can understand what this actually looks like in practice. I’ll tell the AI: “I want to build this app. Here’s what it should do, here’s roughly what it should look like. Figure out the user flow, the design, all of it.” And it does. It writes tens of thousands of lines of code. Then, and this is the part that would have been unthinkable a year ago, it opens the app itself. It clicks through the buttons. It tests the features. It uses the app the way a person would. If it doesn’t like how something looks or feels, it goes back and changes it, on its own. It iterates, like a developer would, fixing and refining until it’s satisfied. Only once it has decided the app meets its own standards does it come back to me and say: “It’s ready for you to test.” And when I test it, it’s usually perfect.
I’m not exaggerating. That is what my Monday looked like this week.
I’ve always been early to adopt AI tools. But the last few months have shocked me. These new AI models aren’t incremental improvements. This is a different thing entirely.
The experience that tech workers have had over the past year, of watching AI go from “helpful tool” to “does my job better than I do”, is the experience everyone else is about to have. Law, finance, medicine, accounting, consulting, writing, design, analysis, customer service. Not in 10ten years. The people building these systems say one to five years. Some say less. The market was spooked enough this month that it wiped out $1 trillion worth of software value in just a week. And given what I’ve seen in just the last couple of months, I see more disruption, and soon.
180754968
submission
ZipNada writes:
AI Swarms Beat Traditional Teams on Speed, Cost & Startup Readiness
11:45 am February 4, 2026 By Julian Horsey
What if you could deploy an army of 100 AI agents to tackle your most complex projects in minutes, and at a fraction of the cost of traditional systems? Universe of AI walks through how the Kimi K2.5 Agent Swarm is redefining what’s possible in AI task management, offering a solution that’s not only 8x cheaper than Claude Opus 4.5 but also up to 4.5 times faster. Imagine launching a startup with a fully functional website, a complete marketing strategy, and detailed competitor analysis, all generated in under 10 minutes. This isn’t just a futuristic concept; it’s a reality that’s reshaping how businesses approach productivity and efficiency.
180391145
submission
ZipNada writes:
The explosion in AI models, software, and agents has raised questions about the impact of the technology on the broader job market as companies find new efficiencies from this new technology.
But according to EY's latest US AI Pulse Survey, just 17% of 500 business executives at US companies that saw productivity gains via AI turned around and cut jobs.
"There's a narrative that we hear quite frequently about companies looking to take that benefit that they're seeing and put it into the financial statements reducing costs, or cutting heads," EY global consulting AI leader Dan Diasio told Yahoo Finance.
"But the data that we asked those 500 executives does not bear that out. That is happening less than one out of five times, and more often they are reinvesting that," he added.
180196635
submission
ZipNada writes:
A new generation of stratospheric balloons and high-altitude uncrewed aerial vehicles (UAVs) could soon connect the world's unconnected with high-speed internet at a fraction of the prices commanded by operators of satellite megaconstellations such as SpaceX's Starlink.
High-altitude platform stations, or HAPS, have been around for a while, but the technology hasn't fully taken off yet. Google spent 10 years trying to develop balloons that would hover in the stratosphere above remote rural areas and beam internet to residents but abandoned that project, called Loon, in 2021, concluding that it couldn't be made sustainable.
Four years later, companies such as World Mobile Stratospheric and Sceye say they are on the verge of making internet-beaming from the stratosphere, the layer of Earth's atmosphere roughly 6 miles to 31 miles (10 to 50 kilometers) above the planet, a reality. Moreover, they claim that their offerings will be better and cheaper than that of satellite megaconstellations in low Earth orbit (LEO), which too have been developed with the promise of connecting the world's unconnected.
178979670
submission
ZipNada writes:
More than 85 veteran climate scientists have pushed back against a Trump administration report downplaying the severity of climate change, submitting more than 400 pages in public comments to the Energy Department on Tuesday.
The department’s Climate Working Group report, released July 29 alongside proposals to deregulate some polluting sectors, was authored by five well-known climate change contrarians and even portrayed climate change as potentially beneficial.
178122443
submission
ZipNada writes:
The essence of search is compression: distilling insights from a vast corpus. Subagents facilitate compression by operating in parallel with their own context windows, exploring different aspects of the question simultaneously before condensing the most important tokens for the lead research agent. Each subagent also provides separation of concerns—distinct tools, prompts, and exploration trajectories—which reduces path dependency and enables thorough, independent investigations. ...
these architectures burn through tokens fast. In our data, agents typically use about 4× more tokens than chat interactions, and multi-agent systems use about 15× more tokens than chats. For economic viability, multi-agent systems require tasks where the value of the task is high enough to pay for the increased performance. Further, some domains that require all agents to share the same context or involve many dependencies between agents are not a good fit for multi-agent systems today. For instance, most coding tasks involve fewer truly parallelizable tasks than research, and LLM agents are not yet great at coordinating and delegating to other agents in real time. We’ve found that multi-agent systems excel at valuable tasks that involve heavy parallelization, information that exceeds single context windows, and interfacing with numerous complex tools.
177126677
submission
ZipNada writes:
Microsoft's latest research identifies a new type of organization known as the Frontier Firm, where on-demand intelligence requirements are managed by hybrid teams of AI agents and humans.
The report identified real productivity gains from implementing AI into organizations, with one of the biggest being filling the capacity gap — as many as 80% of the global workforce, both employees and leaders, report having too much work to do, but not enough time or energy to do it. ...
According to the report, business leaders need to separate knowledge workers from knowledge work, acknowledging that humans who can complete higher-level tasks, such as creativity and judgment, should not be stuck answering emails. Rather, in the same way working professionals say they send emails or create pivot tables, soon they will be able to say they create and manage agents — and Frontier Firms are showing the potential possibilities of this approach. ...
"Everyone will need to manage agents," said Cambron. "I think it's exciting to me to think that, you know, with agents, every early-career person will be able to experience management from day one, from their first job."
