"In every industry, the winners going forward are going to be data and AI companies." See what our CEO @alighodsi has to say about the disruption of #GenerativeAI & the advantage of leading with data + AI
AI
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Skills to Navigate Technology’s Future of Work
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‘Change is the only certainty in tech’: Skills to keep pace with the #FutureofWork https://
bit.ly/45SYhmo via @siliconrepublic -

MetaGPT Redefines Multi-Agent Collaboration for Complex Tasks
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After two weeks off, here's a new video about a very exciting work by @DeepWisdom2019 ! MetaGPT: Redefining Multi-Agent Collaboration for Complex Tasks Learn more: https://
youtu.be/YtxMderNrzU #MetaGPT #GPT #ChatGPT #Agents -

AI and LLMs Streamlining Financial Services and Payments
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How AI And LLMs Are Streamlining Financial Services
#payments #fintech #paymentsolutions @briansolis @Xbond49 @VitalikButerin @DataScienceCtrl @Benioff @johnnosta @IrmaRaste @Tiffani_Bova http://
ow.ly/4hgf30swTtN -
LLMs training on self-generated text as machine learning inbreeding
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LLMs generating new text that they will then use to further train LLMs is the machine learning version of inbreeding.
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Language-to-Rewards System for Robotic Skill Synthesis
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10/ Language to Rewards for Robotic Skill Synthesis – proposes a new language-to-reward system that utilizes LLMs to define optimizable reward parameters to achieve a variety of robotic tasks.https://t.co/8ztl4MMyjS
— DAIR.AI (@dair_ai) 27 août 202310/ Language to Rewards for Robotic Skill Synthesis – proposes a new language-to-reward system that utilizes LLMs to define optimizable reward parameters to achieve a variety of robotic tasks.
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Survey of LLM-Based Autonomous Agents and Applications
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7/ A Survey on LLM-based Autonomous Agents – presents a survey of LLM-based autonomous agents; delivers a systematic review of the field and a summary of various applications of LLM-based AI agents in domains like social science and engineering.
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Prompt2Model: Automated Small Model Training Pipeline
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8/ Prompt2Model – takes a prompt describing a task and trains a small model that is conducive to deployment; the pipeline automatically collects and synthesizes knowledge through three channels: dataset retrieval, dataset generation, and model retrieval.
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LegalBench: Legal Reasoning Benchmark for LLMs
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9/ LegalBench – a collaboratively constructed benchmark for measuring legal reasoning in LLMs; it consists of 162 tasks covering 6 different types of legal reasoning.
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Giraffe: Extended Context Length LLMs from Llama Base Models
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5/ Giraffe – new models that are fine-tuned from base Llama and Llama 2; extends the context length to 4K, 16K, and 32K; explores the space of expanding context lengths in LLMs so it also includes insights useful for practitioners and researchers.