Former Meta AI Pioneer Yann LeCun Raises Over $1 Billion for New Startup - WSJ
<a href="https://news.google.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?oc=5" target="_blank">Former Meta AI Pioneer Yann LeCun Raises Over $1 Billion for New Startup</a> <font color="#6f6f6f">WSJ</font>
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TL;DR: In terms of the potential risks and harms that can come from powerful AI models, hyper-persuasion of individuals is unlikely to be a serious threat at this point in time. I wouldn’t consider this threat path to be very easy for a misaligned AI or maliciously wielded AI to navigate reliably. I would expect that, for people hoping to reduce risks associated with AI models, there are other more impactful and tractable defenses they could work on. I would advocate for more substantive research into the effects of long-term influence from AI companions and dependency, as well as more research into what interventions may work in both one-off and chronic contexts. ----- In this post we’ll explore how bots can actually influence human psychology and decision-making, and what might be done t
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sync : ggml macOS/iOS: macOS Apple Silicon (arm64) macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (ROCm 7.2) Ubuntu x64 (OpenVINO) Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.1 DLLs Windows x64 (Vulkan) Windows x64 (SYCL) Windows x64 (HIP) openEuler: openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph)
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chat : add Granite 4.0 chat template with correct tool_call role mapping ( #20804 ) chat : add Granite 4.0 chat template with correct tool_call role mapping Introduce LLM_CHAT_TEMPLATE_GRANITE_4_0 alongside the existing Granite 3.x template (renamed LLM_CHAT_TEMPLATE_GRANITE_3_X ). The Granite 4.0 Jinja template uses XML tags and maps the assistant_tool_call role to assistant . Without a matching C++ handler, the fallback path emits the literal role assistant_tool_call which the model does not recognize, breaking tool calling when --jinja is not used. Changes: Rename LLM_CHAT_TEMPLATE_GRANITE to LLM_CHAT_TEMPLATE_GRANITE_3_X (preserves existing 3.x behavior unchanged) Add LLM_CHAT_TEMPLATE_GRANITE_4_0 enum, map entry, and handler Detection: + ( or ) → 4.0, otherwise → 3.x Add production Gr

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