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Meet Symbolicai: A Machine Learning Framework that Combines Generative Models and Solvers for Logic-Based Approaches
Generative AI, particularly large language models (LLMs), has significantly impacted various fields and transformed human-computer interactions. However, challenges arise, leading researchers to introduce SymbolicAI, a neuro-symbolic framework. By enhancing LLMs with domain-invariant solvers and leveraging cognitive architecture, SymbolicAI paves the way for flexible applications and lays the groundwork for future studies in self-referential systems and…
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Zyphra Open-Sources BlackMamba: A Novel Architecture that Combines the Mamba SSM with MoE to Obtain the Benefits of Both
Zyphra introduces BlackMamba, a groundbreaking model combining State Space Models (SSMs) and mixture-of-experts (MoE) to address the limitations of traditional transformer models in processing linguistic data. This innovative approach achieves a balance of efficiency and effectiveness, outperforming existing models and offering a scalable solution for natural language processing. The open-source release promotes transparency and collaboration.…
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Language Bias, Be Gone! CroissantLLM’s Balanced Bilingual Approach is Here to Stay
The revolutionary CroissantLLM language model breaks the English-centric bias by offering robust bilingual capabilities in English and French, addressing the limitations in traditional models and the critical need for bilingual language understanding. Developed through collaboration, it sets new benchmarks in bilingual language processing, paving the way for more inclusive NLP applications and inspiring future endeavors…
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AI regulation in the UK leaps forward with white paper consultation
The UK Government has revealed its response to AI innovation and regulation consultations. The white paper proposes a pro-innovation regulatory framework and emphasizes safety, transparency, fairness, and accountability. It aims for context-based regulations tailored to specific AI applications and contexts. The government is investing in AI skills, talent initiatives, and intellectual property protection. The UK…
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AI energy usage and carbon emission stats may be overblown
The ITIF report challenges the narrative of AI’s energy consumption as overblown and emphasizes the need for accurate information. It highlights the increasing efficiency of AI models and hardware, as well as the substitution effects of AI, reducing higher carbon-emitting tasks. The report calls for energy transparency standards for AI models while cautioning against misleading…
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Meta ups the ante in tackling AI deep fake content
Meta has launched new initiatives to increase transparency around AI-generated content on its platforms. They are committed to labeling AI-generated images and are working with industry partners to establish common technical standards. Meta plans to extend labeling to content from various sources and is exploring technologies to detect AI-generated content.
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Microsoft teams up with Semafor to use AI tools for news
Microsoft partners with Semafor to help journalists utilize AI for news creation. Semafor, founded by ex-BuzzFeed and Bloomberg execs, launches “Signals” with Microsoft’s backing, aiming to deliver diverse and up-to-date perspectives on global news. The use of AI tools for news research sparks questions about objectivity and the potential for AI to eventually write stories.
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What babies can teach AI
Researchers at New York University trained an AI model on data from a baby’s perspective in an attempt to mimic human learning. This approach challenged conventional large data set trainings, showing promise in the AI’s ability to match words to objects. This method, inspired by how babies learn, could be key in advancing AI systems.
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AI in CX Automation: It’s Not All or Nothing
In today’s digital age, customers expect seamless and personalized experiences, leading businesses to embrace AI for customer experience (CX) enhancement. AI automation can automate tasks, personalize interactions, and improve customer service, but its adoption can be challenging. This post outlines the benefits of AI in CX, practical implementation tips, and emphasizes its necessity for modern…
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Researchers from EPFL and Meta AI Proposes Chain-of-Abstraction (CoA): A New Method for LLMs to Better Leverage Tools in Multi-Step Reasoning
Recent research by EPFL and Meta introduces the Chain-of-Abstraction (CoA) reasoning method for large language models (LLMs) to enhance multi-step reasoning by efficiently leveraging tools. The method separates general reasoning from domain-specific knowledge, yielding a 7.5% average accuracy increase in mathematical reasoning and a 4.5% increase in Wiki QA, with improved inference speeds.