Reinforcement learning (RL) has fundamentally transformed AI by allowing models to improve performance iteratively through interaction and feedback. When applied to large language models (LLMs), RL opens new avenues for handling tasks that require complex reasoning, such as mathematical problem-solving, coding, and multimodal data interpretation. Traditional methods rely heavily on pretraining with large static datasets. […] The post Kimi k1.5: A Next Generation Multi-Modal LLM Trained with Reinforcement Learning on Advancing AI with Scalable Multimodal Reasoning and Benchmark Excellence appeared first on MarkTechPost. read more

Bagel is a novel AI model architecture that transforms open-source AI development by enabling permissionless contributions and ensuring revenue attribution for contributors. Its design integrates advanced cryptography with machine learning techniques to create a trustless, secure, collaborative ecosystem. Their first platform, Bakery, is a unique AI model fine-tuning and monetization platform built on the Bagel […] The post Beyond Open Source AI: How Bagel’s Cryptographic Architecture, Bakery Platform, and ZKLoRA Drive Sustainable AI Monetization appeared first on MarkTechPost. read more

Tokenization, the process of breaking text into smaller units, has long been a fundamental step in natural language processing (NLP). However, it presents several challenges. Tokenizer-based language models (LMs) often struggle with multilingual text, out-of-vocabulary (OOV) words, and inputs like typos, emojis, or mixed-code text. These issues can reduce model robustness and add complexity to […] The post Meet EvaByte: An Open-Source 6.5B State-of-the-Art Tokenizer-Free Language Model Powered by EVA appeared first on MarkTechPost. read more

The development of TTS systems has been pivotal in converting written content into spoken language, enabling users to interact with text audibly. This technology is particularly beneficial for understanding documents containing complex information, such as scientific papers and technical manuals, which often present significant challenges for individuals relying solely on auditory comprehension. A persistent problem […] The post This AI Paper Introduces MathReader: An Advanced TTS System for Accurate and Accessible Mathematical Document Vocalization appeared first on MarkTechPost. read more

It can significantly enhance LLMs’ problem-solving capabilities by guiding them to think more deeply about complex problems and effectively utilize inference-time computation. Prior research has explored various strategies, including chain-of-thought reasoning, self-consistency, sequential revision with feedback, and search mechanisms guided by auxiliary verifiers or evaluators. Search-based methods, particularly when paired with solution evaluators, leverage additional […] The post Google DeepMind Introduces Mind Evolution: Enhancing Natural Language Planning with Evolutionary Search in Large Language Models appeared first on MarkTechPost. read more

Artificial Intelligence has made significant strides, yet some challenges persist in advancing multimodal reasoning and planning capabilities. Tasks that demand abstract reasoning, scientific understanding, and precise mathematical computations often expose the limitations of current systems. Even leading AI models face difficulties integrating diverse types of data effectively and maintaining logical coherence in their responses. Moreover, […] The post Google AI Releases Gemini 2.0 Flash Thinking model (gemini-2.0-flash-thinking-exp-01-21): Scoring 73.3% on AIME (Math) and 74.2% on GPQA Diamond (Science) Benchmarks appeared first on MarkTechPost. read more

Out of the various methods employed in document search systems, “retrieve and rank” has gained quite some popularity. Using this method, the results of a retrieval model are re-ordered according to a re-ranker. Additionally, in the wake of advancements in generative AI and the development of Large Language Models (LLMs), rankers are now capable of […] The post SlideGar: A Novel AI Approach to Use LLMs in Retrieval Reranking, Solving the Challenge of Bound Recall appeared first on MarkTechPost. read more

Modern NLP applications often demand multi-step reasoning, interaction with external tools, and the ability to adapt dynamically to user queries. Haystack Agents, an innovative feature of the Haystack NLP framework by deepset, exemplifies this new wave of advanced NLP capabilities. Haystack Agents are built to handle scenarios requiring: This article delves deep into the Haystack […] The post What are Haystack Agents? A Comprehensive Guide to Tool-Driven NLP with Code Implementation appeared first on MarkTechPost. read more

Large Language Models (LLMs) have become pivotal in artificial intelligence, powering a variety of applications from chatbots to content generation tools. However, their deployment at scale presents notable challenges. High computational costs, latency, and energy consumption often limit their wider use. Organizations face the difficulty of balancing high throughput with reasonable operating expenses. Additionally, as […] The post Snowflake AI Research Open-Sources SwiftKV: A Novel AI Approach that Reduces Inference Costs of Meta Llama LLMs up to 75% on Cortex AI appeared first on MarkTechPost. read more

Lexicon-based embeddings are one of the good alternatives to dense embeddings, yet they face numerous challenges that restrain their wider adoption. One key problem is tokenization redundancy, whereby subword tokenization breaks semantically equivalent tokens, causing inefficiencies and inconsistencies in embeddings. The other limitation of causal LLMs is unidirectional attention; this means tokens cannot fully leverage […] The post Enhancing Lexicon-Based Text Embeddings with Large Language Models appeared first on MarkTechPost. read more