Marktechpost

APRIL 28, 2024

In-context learning (ICL) in large language models (LLMs) utilizes input-output examples to adapt to new tasks without altering the underlying model architecture. This method has transformed how models handle various tasks by learning from direct examples provided during inference. The problem at hand is the limitation of a few-shot ICL in handling intricate tasks.

Large Language Models 132

Large Language Models AI AI ML 132

Artificial Lawyer

APRIL 28, 2024

For many years there have been efforts to create an easy to use, reliable and affordable legal AI system that will give people advice and even draft documents for them.

AI 134

AI AI 134

Marktechpost

APRIL 28, 2024

Long-context large language models (LLMs) have garnered attention, with extended training windows enabling processing of extensive context. However, recent studies highlight a challenge: these LLMs struggle to utilize middle information effectively, termed the lost-in-the-middle challenge. While the LLM can comprehend the information at the beginning and end of the long context, it often overlooks the information in the middle.

Large Language Models 123

Large Language Models LLM ML Artificial Intelligence 123

Machine Learning Research at Apple

APRIL 28, 2024

Sleep staging is a clinically important task for diagnosing various sleep disorders but remains challenging to deploy at scale because it requires clinical expertise, among other reasons. Deep learning models can perform the task but at the expense of large labeled datasets, which are unfeasible to procure at scale. While self-supervised learning (SSL) can mitigate this need, recent studies on SSL for sleep staging have shown performance gains saturate after training with labeled data from only

Deep Learning 59

Deep Learning 59

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

Marktechpost

APRIL 28, 2024

In artificial intelligence, one common challenge is ensuring that language models can process information quickly and efficiently. Imagine you’re trying to use a language model to generate text or answer questions on your device, but it’s taking too long to respond. This delay can be frustrating and impractical, especially in real-time applications like chatbots or voice assistants.

Python 118

Python LLM Artificial Intelligence Artificial Intelligence 118

Marktechpost

APRIL 28, 2024

In Large language models(LLM), developers and researchers face a significant challenge in accurately measuring and comparing the capabilities of different chatbot models. A good benchmark for evaluating these models should accurately reflect real-world usage, distinguish between different models’ abilities, and regularly update to incorporate new data and avoid biases.

Chatbots 121

Chatbots Large Language Models LLM ML 121

TheSequence

APRIL 28, 2024

Created Using Ideogram Next Week in The Sequence: Edge 391: Our series about autonomous agents continues with the fascinating topic of function calling. We explore UCBerkeley’s research on LLMCompiler for function calling and we review the PhiData framework for building agents. Edge 392: We dive into RAFT, UC Berkeley’s technique for improving RAG scenarios.

Neural Network 52

Neural Network Generative AI Data Science OpenAI 52

Marktechpost

APRIL 28, 2024

In the ever-evolving field of machine learning, developing models that predict and explain their reasoning is becoming increasingly crucial. As these models grow in complexity, they often become less transparent, resembling “black boxes” where the decision-making process is obscured. This opacity is problematic, particularly in sectors like healthcare and finance, where understanding the basis of decisions can be as important as understanding the decisions themselves.

Machine Learning 118

Machine Learning Explainability AI AI 118

Marktechpost

APRIL 28, 2024

Artificial Intelligence (AI) is a rapidly expanding field with new daily applications. However, ensuring these models’ accuracy and dependability continues to be a difficult task. Conventional AI assessment techniques are frequently cumbersome and require extensive manual setup, which impedes ongoing development and disrupts developers’ workflows.

Machine Learning 113

Machine Learning Automation Artificial Intelligence Artificial Intelligence 113

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Marktechpost

APRIL 28, 2024

The popularity of AI has skyrocketed in the past few years, with new avenues being opened up with the rise in the use of large language models (LLMs). Having knowledge of AI has now become quite essential as recruiters are actively looking for candidates with a strong foundation in the same. This article lists the top AI courses for beginners to take to help them make a shift in their careers and gain the necessary skills.

Artificial Intelligence 111

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 111

Marktechpost

APRIL 28, 2024

While 55% of organizations are experimenting with generative AI, only 10% have implemented it in production, according to a recent Gartner poll. LLMs face a major obstacle in transitioning to production due to their tendency to generate erroneous outputs, termed hallucinations. These inaccuracies hinder their utilization in applications requiring correct results.

LLM 130

LLM Chatbots Data Scientist Generative AI 130