Why will large language models never be reliable or useful for automated news se

<table> <tr><td> <a href="https://www.reddit.com/r/OpenAI/comments/1sw0vcf/stanford_researchers_fed_a_language_model_a_dna/"> <img alt="Stanford researchers fed a language model a

<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1srx4i1/new_llm_position_bias_benchmark_does_an_llm_keep/"> <img alt="New LLM Position Bias Benchmark: does

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s59rct/rys_part_3_llms_think_in_geometry_not_language/"> <img alt="RYS Part 3: LLMs think in geometry, not

<!-- SC_OFF --><div class="md"><p>I am trying to understand the current consensus and legal landscape regarding how public data and developer contributions are being utilized by

<!-- SC_OFF --><div class="md"><p>A couple of weeks ago I <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sl5k6d/we_benchmarked_translategemma12b_against_5/">shared the

<!-- SC_OFF --><div class="md"><p>Long time Claude Opus user, but after the recent session limit changes by Anthropic, I am seriously considering trying Chinese models for coding.

<!-- SC_OFF --><div class="md"><p>I need SOTA ai at like 2k TPS with tiny latency so that I can get time to first answer token under 3 seconds for real time replies with full COT

<!-- SC_OFF --><div class="md"><p>One thing we’ve been noticing lately is that a surprisingly large percentage of day-to-day AI workflows no longer seem to require frontier-scale