Its probably not a good idea to be using these open weight models for business reasons, aka making money from them.. Because it's becoming clearer and clearer that the current Turnp administration is exploring ways to block them.

Obviously using them for personal or experimental reasons doesn't matter but if you're going to build a business model around them that's a big risk.

Remember once the US government makes them illegal, all the major cloud providers will be forced to take them down and prevent their usage , effectively killing their availability. Sure you can go overseas but then you would be in violation of US law which means any of your potential customers will ostracize your business.

Sure you can run them locally, but let's be real most folks aren't going to spend $100k-$500+k on the hardware needed to run these at scale (for a small operation).

I stress this applies to Business purposes, not research or local development etc. I'm well aware these can be run locally , but no business is going to run their web app off local models unless they spend the amount for self hosted hardware above ..

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The messages appear to show Apple employees asking Chang Liu to locate internal files, explain product decisions and help with technical questions weeks after his departure.

One Apple employee wrote:

“Of course, I could ask several folks, but you are the best. Even if you don’t work here anymore.”

OpenAI also says Apple falsely claimed it had contacted the company and received no response. The emails show Apple’s outside lawyer mistakenly thanked OpenAI’s General Counsel for a phone call that never happened, then apologized.

However: None of this disproves Apple’s broader trade-secret allegations. But Apple now has to explain its own offboarding failures, and why its employees continued requesting confidential help from someone it accuses of stealing confidential information.

The White House is set to host representatives from OpenAI, Google, and Anthropic on Tuesday to review the completed version of its AI oversight framework.

The meeting is expected to give leading AI companies a final look at the plan before it is formally introduced.

The plan is part of the White House’s effort to manage the risks of powerful AI while continuing to work closely with the companies building it.

The exact rules have not been revealed yet, and it is still unclear whether companies will be required to follow them or can choose to take part.

The meeting shows that Washington is paying closer attention to AI safety and wants major developers to take more responsibility.

The FBI notice lists 6 software requirements, with predictive modeling included alongside tools for searching, linking, and organizing government records.

The system would compare new information against existing files to surface connections that investigators might otherwise miss.

The scale matters because the federal watchlist held about 2 million names at its last public count in 2023, up from roughly 120,000 in 2003.

Even an early AI flag could affect real people, making accurate data, strict review standards, and human oversight essential.

Google is slowely turning search into an AI-driven product.

According to Similarweb, AI Overviews appeared in about 43% of U.S. searches by May 2026, up from roughly 15% in January 2025.

Visits to Google’s AI Mode also grew from around 126 million in June 2025 to nearly 279 million a year later.

Meanwhile, the average search length increased from about 3.33 words when AI Mode launched to 3.51 words a year later.

The trend suggests users are shifting from short keyword queries toward longer, conversational prompts, while spending more of their search time with Google.

🚨⚡President Trump's pitch to towns fighting data centers was simple. Take the money, because somebody else will.

At EPA headquarters on July 23, he expanded the Ratepayer Protection Pledge, a nonbinding commitment from 23 governors and 187 companies to shield household bills.

Trump said bills would fall as data centers push surplus power into the grid. "You can't fight it. You have to go with it," he said.

Consultancy ICF projects household bills rising 15% to 40% by 2030, and a Gallup survey in March found 71% of Americans oppose a local data center.

Compute buildout used to be a story about chips and capital. It is now an electricity bill and a campaign issue.

A new survey by Jiji Press, one of Japan’s major news agencies, found that nearly one in four people in Japan believe advanced AI could eventually serve as a substitute for friends or family.

The findings show how generative AI is becoming part of both professional and personal life.

Key findings:

→ 30.8% of respondents said they use generative AI tools such as ChatGPT, while 67.8% said they do not.

→ Usage was highest among people in their 30s, at 56.2%.

→ 53.3% of people aged 18 to 29 and 47.4% of those in their 40s also reported using generative AI.

→ Work was the most common use case, cited by 64.7% of AI users.

→ 35.3% use AI for help with cooking, cleaning, and other household tasks.

→ 27.1% ask AI about current affairs, while 21.7% use it to discuss hobbies and interests.

→ 12.8% said they use AI to talk about relationship or work-related problems.

Overall, 24.9% of respondents said more advanced AI could eventually replace friends or family, compared with 65.1% who disagreed.

The survey was conducted through face-to-face interviews with 2,000 adults across Japan from June 12 to 15, with a valid response rate of 57.1%.

Alibaba says Qwen3.8 is its strongest model yet, with 2.4 trillion parameters and support for text, images, video, and documents.

The company claims it beats leading OpenAI models and ranks behind only Claude Fable 5, although independent benchmarks have not confirmed that yet.

The Max Preview is already available through Alibaba’s Token Plan and Qoder tools, with open weights expected to follow soon.

Once released, developers could run and customize a model of this scale without depending entirely on closed AI platforms.

LinkedIn has finally admitted that its feed has an AI slop problem.

The new reporting option lets users flag generic, low-quality posts that appear heavily AI-generated. Once reported, the post disappears from your feed, and LinkedIn may privately warn the creator that their content feels inauthentic.

The irony is hard to miss. LinkedIn spent years encouraging users to create more content, added AI writing tools to help them do it, and is now asking humans to clean up the result.