ML applications

Meta AI Released MobileLLM-R1: A Edge Reasoning Model with less than 1B Parameters and Achieves 2x–5x Performance Boost Over Other Fully Open-Source AI Models

ML applications

3 Min Read

Meta AI Released MobileLLM-R1: A Edge Reasoning Model with less than 1B Parameters and Achieves 2x–5x Performance Boost Over Other Fully Open-Source AI Models

By Editorial Team

September 15, 2025

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UT Austin and ServiceNow Research Team Releases AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

ML applications

5 Min Read

UT Austin and ServiceNow Research Team Releases AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

By Editorial Team

September 14, 2025

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Google AI Releases VaultGemma: The Largest and Most Capable Open Model (1B-parameters) Trained from Scratch with Differential Privacy

ML applications

4 Min Read

Google AI Releases VaultGemma: The Largest and Most Capable Open Model (1B-parameters) Trained from Scratch with Differential Privacy

By Editorial Team

September 13, 2025

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BentoML Released llm-optimizer: An Open-Source AI Tool for Benchmarking and Optimizing LLM Inference

ML applications

3 Min Read

BentoML Released llm-optimizer: An Open-Source AI Tool for Benchmarking and Optimizing LLM Inference

By Editorial Team

September 12, 2025

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Meet mmBERT: An Encoder-only Language Model Pretrained on 3T Tokens of Multilingual Text in over 1800 Languages and 2–4× Faster than Previous Models

ML applications

4 Min Read

Meet mmBERT: An Encoder-only Language Model Pretrained on 3T Tokens of Multilingual Text in over 1800 Languages and 2–4× Faster than Previous Models

By Editorial Team

September 11, 2025

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MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models

ML applications

6 Min Read

MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models

By Editorial Team

September 9, 2025

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A New MIT Study Shows Reinforcement Learning Minimizes Catastrophic Forgetting Compared to Supervised Fine-Tuning

ML applications

4 Min Read

A New MIT Study Shows Reinforcement Learning Minimizes Catastrophic Forgetting Compared to Supervised Fine-Tuning

By Editorial Team

September 8, 2025

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Implementing DeepSpeed for Scalable Transformers: Advanced Training with Gradient Checkpointing and Parallelism

ML applications

12 Min Read

Implementing DeepSpeed for Scalable Transformers: Advanced Training with Gradient Checkpointing and Parallelism

By Editorial Team

September 8, 2025

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Meta Superintelligence Labs Introduces REFRAG: Scaling RAG with 16× Longer Contexts and 31× Faster Decoding

ML applications

4 Min Read

Meta Superintelligence Labs Introduces REFRAG: Scaling RAG with 16× Longer Contexts and 31× Faster Decoding

By Editorial Team

September 7, 2025

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From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem

ML applications

4 Min Read

From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem

By Editorial Team

September 7, 2025

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ML applications

Meta AI Released MobileLLM-R1: A Edge Reasoning Model with less than 1B Parameters and Achieves 2x–5x Performance Boost Over Other Fully Open-Source AI Models

UT Austin and ServiceNow Research Team Releases AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

Google AI Releases VaultGemma: The Largest and Most Capable Open Model (1B-parameters) Trained from Scratch with Differential Privacy

BentoML Released llm-optimizer: An Open-Source AI Tool for Benchmarking and Optimizing LLM Inference

Meet mmBERT: An Encoder-only Language Model Pretrained on 3T Tokens of Multilingual Text in over 1800 Languages and 2–4× Faster than Previous Models

MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models

A New MIT Study Shows Reinforcement Learning Minimizes Catastrophic Forgetting Compared to Supervised Fine-Tuning

Implementing DeepSpeed for Scalable Transformers: Advanced Training with Gradient Checkpointing and Parallelism

Meta Superintelligence Labs Introduces REFRAG: Scaling RAG with 16× Longer Contexts and 31× Faster Decoding

From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem

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