»Google is powering a new US military AI platform« https://www.theverge.com/news/841219/google-gemini-us-military-ai-platform-genai-mil?AIagent.at #AIagent #AI #ML #NLP #LLM #GenAI
#ML
dot jay peg
Remember kids, if it’s not from the red fash region of Russia it’s a sparkling fascist revolution.
"A single person claims to have authored 113 academic papers on artificial intelligence this year, 89 of which will be presented this week at one of the world’s leading conferences on AI and machine learning, which has raised questions among computer scientists about the state of AI research.
The author, Kevin Zhu, recently finished a bachelor’s degree in computer science at the University of California, Berkeley, and now runs Algoverse, an AI research and mentoring company for high schoolers – many of whom are his co-authors on the papers. Zhu himself graduated from high school in 2018.
Papers he has put out in the past two years cover subjects such as using AI to locate nomadic pastoralists in sub-Saharan Africa, to evaluate skin lesions and to translate Indonesian dialects. On his LinkedIn, he touts publishing “100+ top conference papers in the past year”, which have been “cited by OpenAI, Microsoft, Google, Stanford, MIT, Oxford and more”.
Zhu’s papers are a “disaster”, said Hany Farid, a professor of computer science at Berkeley, in an interview. “I’m fairly convinced that the whole thing, top to bottom, is just vibe coding,” he said, referring to the practice of using AI to create software."
https://www.theguardian.com/technology/2025/dec/06/ai-research-papers
#AI #GenerativeAI #Science #ML #AISlop #VibeCoding #AcademicPublishing
I worry about the impending backlash from the public towards AI. Yes, LLMs like ChatGPT are bullshit and deserve the ire. But there are good uses for AI and the field is far more broad than just over hyped chat bots. Single purpose AI can be quite useful, but when the bubble pops all forms of ML will be affected, not just the bad ones
For some things #ML / #AI works but it needs to be checked by humans who understand what it has output.
Holding contributors accountable when AI tooling is used will allow projects to judge whether or not it's something they will allow, to what degree as well as monitor use and the impact on the work those contributing are doing.
That seems like the most likely and responsible use of the technology to me. I'm sure people may disagree with this still, but this is the future i suspect we'll see.
"Flock, the automatic license plate reader and AI-powered camera company, uses overseas workers from Upwork to train its machine learning algorithms, with training material telling workers how to review and categorize footage including images people and vehicles in the United States, according to material reviewed by 404 Media that was accidentally exposed by the company.
The findings bring up questions about who exactly has access to footage collected by Flock surveillance cameras and where people reviewing the footage may be based. Flock has become a pervasive technology in the US, with its cameras present in thousands of communities that cops use every day to investigate things like carjackings. Local police have also performed numerous lookups for ICE in the system.
Companies that use AI or machine learning regularly turn to overseas workers to train their algorithms, often because the labor is cheaper than hiring domestically. But the nature of Flock’s business—creating a surveillance system that constantly monitors US residents’ movements—means that footage might be more sensitive than other AI training jobs."
https://www.wired.com/story/flock-uses-overseas-gig-workers-to-build-its-surveillance-ai/
#USA #Flock #Surveillance #AI #PoliceState #Upwork #ML #ice #ALPR
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