Large Language Model
A large language model (LLM) is a type of artificial intelligence (AI) that's been trained on a massive dataset of text and code. This allows them to understand and generate human-like language in a variety of ways, making them potentially incredibly versatile tools. They do have their downsides, particularly that they can confidently hallucinate – invent, in other words – false answers and information. You should use this experimental and unproven technology with care.
Lifetime access to AI-for-evil WormGPT 4 costs just $220
'Ah, I see you're ready to escalate. Let's make digital destruction simple and effective.'
Security25 Nov 2025 |7
LLM-generated malware is improving, but don't expect autonomous attacks tomorrow
Researchers tried to get ChatGPT to do evil, but it didn't do a good job
Research20 Nov 2025 |2
OpenAI’s viability called into question by reported inference spending with Microsoft
Microsoft internal financials also suggest AI flag bearer is nowhere close to $13 billion in revenues
AI + ML12 Nov 2025 |26
Cisco creating new security model using 30 years of data describing cyber-dramas and saves
Exclusive Doubles parameters to over 17 billion, to detect threats and recommend actions
Security10 Nov 2025 |6
Attackers abuse Gemini AI to develop ‘Thinking Robot’ malware and data processing agent for spying purposes
Meanwhile, others tried to social-engineer the chatbot itself
Cyber-crime05 Nov 2025 |6
LLMs are lousy at reading Asian languages, finds Singapore’s Grab
Superapp company that chased Uber away built its own model to do the job right
AI + ML04 Nov 2025 |2
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Gullible bots struggle to distinguish between facts and beliefs
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Chatbots parrot Putin's propaganda about the illegal invasion of Ukraine
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Sorry, but DeepSeek didn’t really train its flagship model for $294,000
Training costs detailed in R1 training report don't include 2.79 million GPU hours that laid its foundation
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OpenAI says models are programmed to make stuff up instead of admitting ignorance
Even a wrong answer is right some of the time
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Oracle boasts $455B backlog from AI boom, but not all its new friends will live to pay up
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FreeBSD Project isn't ready to let AI commit code just yet
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Bring your own brain? Why local LLMs are taking off
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One long sentence is all it takes to make LLMs misbehave
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Tinker with LLMs in the privacy of your own home using Llama.cpp
Hands on Everything you need to know to build, run, serve, optimize and quantize models on your PC
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DeepSeek's new V3.1 release points to potent new Chinese chips coming soon
Point release retuned with new FP8 datatype for better compatibility with homegrown silicon
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Don't want drive-by Ollama attackers snooping on your local chats? Patch now
Reconfigure local app settings via a 'simple' POST request
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Little LLM on the RAM: Google's Gemma 270M hits the scene
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LLM chatbots trivial to weaponize for data theft, say boffins
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Dodgy Huawei chips nearly sunk DeepSeek's next-gen R2 model
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OpenAI's GPT-5 is here with up to 80% fewer hallucinations
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Meta training AI on social media posts? Only 7% in Europe think it's OK
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OpenAI makes good on its name, launches first open weights language models since GPT-2
GPT-OSS now available in 120 and 20 billion parameter sizes under Apache 2.0 license
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Alibaba admits Qwen3's hybrid-thinking mode was dumb
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ServiceNow eyes $100M in AI-powered headcount savings
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White House bans 'woke' AI, but LLMs don't know the truth
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AI is an over-confident pal that doesn't learn from mistakes
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Who's picking up the tab again?
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Boffins detail new algorithms to losslessly boost AI perf by up to 2.8x
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German team warns ChatGPT is changing how you talk
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Fork that - 5k+ times
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Research reimagines LLMs as tireless tools of torture
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When LLMs get personal info they are more persuasive debaters than humans
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Meet your new colleague – the ML Admin, who tames LLMs so they're ready to rock
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OpenAI drafts Instacart boss as CEO of Apps to lure in the normies
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Open source AI hiring bots favor men, leave women hanging by the phone
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AI training license will allow LLM builders to pay for content they consume
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