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.

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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.

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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.

Large Language Models 66

Large Language Models Chatbots LLM ML 66

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 58

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 58

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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.

Automation 55

Automation Machine Learning Artificial Intelligence Artificial Intelligence 55