Sat.Jun 15, 2024

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Harvard Neuroscientists and Google DeepMind Create Artificial Brain in Virtual Rat

Unite.AI

In an impressive collaboration, researchers at Harvard University have joined forces with Google DeepMind scientists to create an artificial brain for a virtual rat. Published in Nature , this innovative breakthrough opens new doors in studying how brains control complex movement using advanced AI simulation techniques. Building the Virtual Rat Brain To construct the virtual rat's brain, the research team utilized high-resolution data recorded from real rats.

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TensorFlow vs Keras: Which is a Better Library?

Analytics Vidhya

Introduction Tensorflow and Keras are well-known machine learning frameworks for data scientists or developers. In the upcoming sections we will examine the pros, downsides, and differences between these libraries. We will also explore Tensorflow vs Keras in this article. Overview What is TensorFlow? TensorFlow is a robust end-to-end Deep Learning framework.

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Optimizing for Choice: Novel Loss Functions Enhance AI Model Generalizability and Performance

Marktechpost

Artificial intelligence (AI) is focused on developing systems capable of performing tasks that typically require human intelligence, such as learning, reasoning, problem-solving, perception, and language understanding. These technologies have various applications across various industries, including healthcare, finance, transportation, and entertainment, making it a vital area of research and development.

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How to uncover and avoid structural biases in evaluating your Machine Learning/NLP projects

Explosion

This talk highlights common pitfalls that occur when evaluating ML and NLP approaches. It provides comprehensive advice on how to set up a solid evaluation procedure in general, and dives into a few specific use-cases to demonstrate artificial bias that unknowingly can creep in.

NLP 52
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The AI Superhero Approach to Product Management

Speaker: Conrado Morlan

In this engaging and witty talk, we’ll explore how artificial intelligence can transform the daily tasks of product managers into streamlined, efficient processes. Using the lens of a superhero narrative, we’ll uncover how AI can be the ultimate sidekick, aiding in decision-making, enhancing productivity, and boosting innovation. Attendees will leave with practical tools and actionable insights, motivated to embrace AI and leverage its potential in their work. 🦸 🏢 Key objectives:

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With 700,000 Large Language Models (LLMs) On Hugging Face Already, Where Is The Future of Artificial Intelligence AI Headed?

Marktechpost

Large Language Models (LLMs) have taken over the Artificial Intelligence (AI) community in recent times. In a Reddit post, a user recently brought attention to the startling quantity of over 700,000 large language models on Hugging Face, which sparked an argument about their usefulness and potential. This article is based on a Reddit thread, and it explores the repercussions of having so many models and the community’s viewpoint on their management and value.

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Scaling AI Models: Combating Collapse with Reinforced Synthetic Data

Marktechpost

As AI-generated data increasingly supplements or even replaces human-annotated data, concerns have arisen about the degradation in model performance when models are iteratively trained on synthetic data. Model collapse refers to this phenomenon where a model’s performance deteriorates significantly when trained on synthesized data generated using the model.

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‘Believe in Something Unconventional, Something Unexplored,’ NVIDIA CEO Tells Caltech Grads

NVIDIA

NVIDIA founder and CEO Jensen Huang on Friday encouraged Caltech graduates to pursue their craft with dedication and resilience — and to view setbacks as new opportunities. “I hope you believe in something. Something unconventional, something unexplored. But let it be informed, and let it be reasoned, and dedicate yourself to making that happen,” he said.

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NVIDIA AI Introduces Nemotron-4 340B: A Family of Open Models that Developers can Use to Generate Synthetic Data for Training Large Language Models (LLMs)

Marktechpost

NVIDIA has recently unveiled the Nemotron-4 340B , a groundbreaking family of models designed to generate synthetic data for training large language models (LLMs) across various commercial applications. This release marks a significant advancement in generative AI, offering a comprehensive suite of tools optimized for NVIDIA NeMo and NVIDIA TensorRT-LLM and includes cutting-edge instruct and reward models.

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Lightski: An AI Startup that Lets You Embed ChatGPT Code Interpreter in Your App

Marktechpost

These days, an embedded analytics solution can cost six figures. Users are never satisfied, regardless of how much effort is put in. They often express frustration with the complicated user interface or wish for more advanced analytics. It could have been better; however, most customers ended up extracting the data and doing their analyses. A natural language interface and strong code-based analysis are now possible thanks to recent breakthroughs in AI that eliminate this trade-off.

ChatGPT 115
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Provide Real Value in Your Applications with Data and Analytics

The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.

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Thread: A Jupyter Notebook that Combines the Experience of OpenAI’s Code Interpreter with the Familiar Development Environment of a Python Notebook

Marktechpost

The digital age demands for automation and efficiency in the domain of software and applications. Automating repetitive coding tasks and reducing debugging time frees up programmers’ time for more strategic work. This can be especially beneficial for businesses and organizations that rely heavily on software development. The recently released AI-powered Python notebook Thread addresses the challenge of improving coding efficiency, reducing errors, and enhancing the overall coding experienc

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Researchers from Stanford and Duolingo Demonstrate Effective Strategies for Generating at a Desired Proficiency Level Using Proprietary Models such as GPT4 and Open-Source Techniques

Marktechpost

Controlling the language proficiency levels in texts generated by large language models (LLMs) is a significant challenge in AI research. Ensuring that generated content is appropriate for various proficiency levels is crucial for applications in language learning, education, and other contexts where users may not be fully proficient in the target language.

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A New Google Study Presents Personal Health Large Language Model (Ph-Llm): A Version Of Gemini Fine-Tuned For Text Understanding Numerical Time-Series Personal Health Data

Marktechpost

A wide variety of areas have demonstrated excellent performance for large language models (LLMs), which are flexible tools for language generation. The potential of these models in medical education, research, and clinical practice is not just immense, but transformative, offering a promising future where natural language serves as an interface. Enhanced with healthcare-specific data, LLMs excel in medical question-answering, detailed EHR analysis, medical image differential diagnosis, standardi

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MAGPIE: A Self-Synthesis Method for Generating Large-Scale Alignment Data by Prompting Aligned LLMs with Nothing

Marktechpost

Artificial intelligence’s large language models (LLMs) have become essential tools due to their ability to process and generate human-like text, enabling them to perform various tasks. These models rely heavily on high-quality instruction datasets for fine-tuning, which enhances their ability to understand and follow complex instructions. The success of LLMs in various applications, from chatbots to data analysis, hinges on the diversity and quality of the instruction data they are trained

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Demystifying DAPs: A Practical Guide to Digital Adoption Success

Speaker: Pulkit Agrawal

Digital Adoption Platforms (DAPs) are revolutionizing the way organizations interact with and optimize their software applications. As digital transformation continues to accelerate, DAPs have become essential tools for enhancing user engagement and software efficiency. This session is your guide into the robust world of DAPs, exploring their origins, evolution, and the current trends shaping their development.

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Enhancing Trust in Large Language Models: Fine-Tuning for Calibrated Uncertainties in High-Stakes Applications

Marktechpost

Large language models (LLMs) face a significant challenge in accurately representing uncertainty over the correctness of their output. This issue is critical for decision-making applications, particularly in fields like healthcare where erroneous confidence can lead to dangerous outcomes. The task is further complicated by linguistic variances in freeform generation, which cannot be exhaustively accounted for during training.