Aayush Mittal

When it comes to natural language processing (NLP) and information retrieval, the ability to efficiently and accurately retrieve relevant information is paramount. As the field continues to evolve, new techniques and methodologies are being developed to enhance the performance of retrieval systems, particularly in the context of

In the rapidly advancing field of large language models (LLMs), a new powerful model has emerged – DBRX, an open source model created by Databricks . This

The field of artificial intelligence (AI) continues to push the boundaries of what was once thought impossible. From self-driving cars to language models that can engage in human-like conversations, AI is rapidly transforming various industries, and software development is no exception. The emergence of AI-powered software engineers, such as SWE-Agent developed by Princeton University's NLP...

Meta has recently released Llama 3 , the next generation of its state-of-the-art open source large language model (LLM). Building on the foundations

Enterprises today are increasingly exploring ways to leverage large language models (LLMs) to boost productivity and create intelligent applications. However, many of the available LLM options are generic models not tailored for specialized enterprise needs like data analysis, coding, and task automation. Enter

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP) by demonstrating remarkable capabilities in generating human-like text, answering questions, and assisting with a wide range of language-related tasks. At the core of these powerful models lies the decoder-only transformer architecture, a variant of the original transformer architecture proposed in the seminal...

Microsoft has recently unveiled its latest lightweight language model called Phi-3 Mini, kickstarting a trio of compact AI models that are designed to deliver state-of-the-art performance while being small enough to run efficiently on devices with limited computing resources. At just 3.8 billion parameters, Phi-3 Mini is a fraction of the size of AI giants...

Large language models (LLMs) like GPT-4, Bloom, and LLaMA have achieved remarkable capabilities by scaling up to billions of parameters. However, deploying these massive models for inference or fine-tuning is challenging due to their immense memory requirements. In this technical blog, we will explore techniques for estimating and optimizing memory consumption during LLM inference and...

Graphs are data structures that represent complex relationships across a wide range of domains, including social networks, knowledge bases, biological systems, and many more. In these graphs, entities are represented as nodes, and their relationships are depicted as edges. The ability to effectively represent and reason about these intricate relational structures is crucial for enabling...

For over two decades, Sepp Hochreiter's pioneering Long Short-Term Memory (LSTM) architecture has been instrumental in numerous deep learning breakthroughs and real-world applications. From generating natural language to powering speech recognition systems, LSTMs have been a driving force behind the AI revolution. However, even the creator of LSTMs recognized their inherent limitations that prevented them...