Unite.AI

JUNE 15, 2024

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.

Neural Network 328

Neural Network Robotics Algorithm Explainability 328

Analytics Vidhya

JUNE 15, 2024

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.

Data Scientist 254

Data Scientist Deep Learning Machine Learning Data Science 254

Marktechpost

JUNE 15, 2024

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.

AI Modeling 133

AI Modeling Large Language Models AI AI 133

Explosion

JUNE 15, 2024

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

NLP Machine Learning ML 52

Speaker: Jay Allardyce

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Business Intelligence

Marktechpost

JUNE 15, 2024

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.

Large Language Models 131

Large Language Models Artificial Intelligence Artificial Intelligence Categorization 131

Marktechpost

JUNE 15, 2024

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.

AI Modeling 130

AI Modeling Prompt Engineer Prompt Engineering Large Language Models 130

NVIDIA

JUNE 15, 2024

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.

Deep Learning 88

Deep Learning Robotics Algorithm Generative AI 88

Marktechpost

JUNE 15, 2024

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 113

ChatGPT ETL Data Scientist Artificial Intelligence 113

Marktechpost

JUNE 15, 2024

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.

Large Language Models 113

Large Language Models LLM AI AI 113

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Marktechpost

JUNE 15, 2024

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

Python 104

Python Natural Language Processing Large Language Models OpenAI 104

Marktechpost

JUNE 15, 2024

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.

Large Language Models 85

Large Language Models LLM Automation AI Tools 85

Marktechpost

JUNE 15, 2024

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

Large Language Models 86

Large Language Models LLM Automation Data Integration 86

Marktechpost

JUNE 15, 2024

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

Prompt Engineer 134

Prompt Engineer Prompt Engineering Auto-complete Large Language Models 134

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

Generative AI

Marktechpost

JUNE 15, 2024

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.

Large Language Models 130

Large Language Models LLM ML AI 130