Sat.Mar 30, 2024

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Guide to Fine-tuning Gemini for Masking PII Data

Analytics Vidhya

Introduction With the advent of Large Language Models (LLMs), they have permeated numerous applications, supplanting smaller transformer models like BERT or Rule Based Models in many Natural Language Processing (NLP) tasks. LLMs are versatile, capable of handling tasks such as Text Classification, Summarization, Sentiment Analysis, and Topic Modelling, owing to their extensive pre-training.

BERT 309
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Groundbreaking Biomimetic Olfactory Chips Use AI to Enable Robots to Smell

Unite.AI

The development of artificial olfactory sensors has been a long-standing challenge for researchers worldwide. Creating electronic noses (e-noses) that can effectively discern complex odorant mixtures, similar to the biological olfactory system, has proven difficult due to issues with miniaturization and recognition capabilities. However, a research team led by Prof.

Robotics 316
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Databricks DBRX: The Open-Source LLM Taking on the Giants

Analytics Vidhya

Large Language Models (LLMs) are the driving force behind AI revolution, but the game just got a major plot twist. Databricks DBRX, a groundbreaking open-source LLM, is here to challenge the status quo. Outperforming established models and going toe-to-toe with industry leaders, DBRX boasts superior performance and efficiency. Deep dive into the world of LLMs […] The post Databricks DBRX: The Open-Source LLM Taking on the Giants appeared first on Analytics Vidhya.

LLM 286
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A Builder's Guide to Evals for LLM-based Applications

Eugene Yan

Evals for classification, summarization, translation, copyright regurgitation, and toxicity.

LLM 220
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Adaptive-RAG: Enhancing Large Language Models by Question-Answering Systems with Dynamic Strategy Selection for Query Complexity

Marktechpost

In the evolving field of Retrieval-Augmented Generation (RAG), the quest for refining question-answering (QA) capabilities remain at the forefront of research. Integrating external knowledge bases with large language models (LLMs) has unlocked new avenues for enhancing the accuracy of responses in various tasks. However, a challenge that persists is the model’s ability to efficiently navigate the spectrum of query complexities, ranging from straightforward questions to intricate multi-step

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Mini-Gemini: A Simple and Effective Artificial Intelligence Framework Enhancing multi-modality Vision Language Models (VLMs)

Marktechpost

Vision Language Models (VLMs) emerge as a result of a unique integration of Computer Vision (CV) and Natural Language Processing (NLP). This integration seeks to mimic human-like understanding by interpreting and generating content that marries images with words, giving rise to a complex challenge that has piqued the interest of researchers worldwide.

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Mamba ands DSPy explained!

Bugra Akyildiz

Articles We covered Mamba as an introduction in one of the previous newsletter: This article from Gradient expands a lot more about the advantages and technical details with comparison to Transformers: Limitations of Transformers(now it should be obvious to everyone as talked in the previous newsletter!): Quadratic Bottleneck: Transformers use an attention mechanism that allows every token to look at every other token in the sequence, leading to a quadratic increase in training time complexity f

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This AI Paper Introduces InternLM2: An Open-Source Large Language Model LLM that Demonstrates Exceptional Performance in both Subjective and Objective Evaluations

Marktechpost

In the ever-evolving landscape of artificial intelligence, the quest for more advanced and capable language models has been a driving force. Researchers at Shanghai AI Laboratory, SenseTime Group, The Chinese University of Hong Kong, and Fudan University have unveiled InternLM2 , a remarkable open–source achievement in Large Language Models (LLMs). Let’s start by addressing the problem at hand.

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How to Use Prompt Engineering in ChatGPT? Key Insights and Tips

Marktechpost

Large Language Models (LLMs) are now a crucial component of innovation, with ChatGPT being one of the most popular ones developed by OpenAI. Its ability to generate text responses resembling human-like language has become essential for various applications such as chatbots, content creation, and customer service. However, to get the best results from ChatGPT, one must master the art of prompt engineering.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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RakutenAI-7B: A Suite of Japanese-Oriented Large Language Models that Achieve the Great Performance on the Japanese Language Model

Marktechpost

Natural Language Processing (NLP) models are pivotal for various applications, from translation services to virtual assistants. They enhance the ability to comprehend and generate human-like responses. These models have become increasingly sophisticated and offer nuanced understanding and interaction capabilities as technology advances. A persisting challenge in NLP is the development of models that can understand and generate text in languages other than English, such as Japanese.

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Top Ten Python Libraries for Machine Learning and Deep Learning in 2024

Marktechpost

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier ways to build, train, and deploy models. Below are the top ten Python libraries that stand out in AI development. TensorFlow TensorFlow is a powerful open-source library that facilitates numerical computation and accelerates the machine learning process.

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7 GPTs That Are Game-Changing For Entrepreneurs 

Marktechpost

In the rapidly evolving world of artificial intelligence (AI), entrepreneurs find themselves at the forefront of innovation and efficiency. The advent of generative pre-trained transformers (GPT) has introduced a plethora of tools designed to streamline the entrepreneurial journey. Among these advancements, seven GPT applications stand out, promising to significantly impact how entrepreneurs operate, analyze data, and communicate their ideas.

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This AI Paper from Durham University Evaluates GPT-3.5 and GPT-4’s Performance Against Student Coders in Physics

Marktechpost

Coding courses have cemented their place as a cornerstone of Science Technology Engineering Mathematics (STEM) education. These courses, spanning a broad spectrum from the foundational syntax of programming languages to the intricacies of algorithm development, are instrumental in arming students with the skills necessary for thriving in the digital economy.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Meet Ratchet: A Web-First, Cross-Platform Machine Learning Developer Toolkit

Marktechpost

Integrating artificial intelligence (AI) into applications has become necessary for developers looking to stay ahead. However, making AI work seamlessly with web and mobile platforms takes work. Issues such as compatibility across different devices, the need for efficient computation without draining resources, and the complexities involved in implementing AI models make the process daunting.

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AgentStudio: An Open Toolkit for Developing General-Purpose Agents Capable of Operating in Digital Worlds

Marktechpost

In our rapidly evolving digital landscape, the quest to develop autonomous virtual agents capable of navigating the vast expanse of software tools has captured the imagination of researchers and tech enthusiasts alike. However, this pursuit has been hindered by formidable obstacles—the scarcity of comprehensive infrastructure for building and evaluating agents in real-world environments and the pressing need to assess their fundamental abilities holistically.

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Meet Dragoneye: An AI Startup Revolutionizing Computer Vision for Developers

Marktechpost

In the rapidly evolving world of technology, where the demand for sophisticated computer vision (CV) applications is soaring, a new startup named Dragoneye is making waves. Aimed at developers looking to integrate cutting-edge CV capabilities into their applications without the need for extensive machine learning (ML) expertise or training data, Dragoneye promises to transform the landscape of computer vision development.

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Pollen-Vision: An Artificial Intelligence Library Empowering Robots with the Autonomy to Grasp Unknown Objects

Marktechpost

In an era where robotics and artificial intelligence (AI) seamlessly blend to enhance technological capabilities, a groundbreaking development has emerged, promising to redefine how robots perceive and interact with their surroundings. Meet the Pollen-Vision library that offers a unified interface for Zero-Shot vision models tailored explicitly for robotics.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.