Analytics Vidhya

OCTOBER 20, 2024

Looking to enhance the performance of your agent-based systems? One of the most effective strategies is to structure both the inputs and intermediate outputs shared between agents. In this article, we’ll explore how to organize inputs, manage placeholders for passing data, and structure outputs to ensure that each agent delivers the desired results.

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Python AI AI 219

IBM Journey to AI blog

OCTOBER 20, 2024

IBM today announced new advances in AI technology that continue to make it easier for businesses to transform with choice, openness and trust. Most notable is the launch of powerful new Granite models, which outperform or match the performance of similarly sized models from leading model providers. We also introduced the next generation of watsonx Code Assistant for general purpose coding and debuted new tools for building and deploying AI applications and agents, all designed with specific ente

AI 201

AI AI Generative AI Artificial Intelligence 201

Ehud Reiter

OCTOBER 20, 2024

I’m preparing supporting material for my new book on NLG , and I realised while doing this that I’ve written very little about a very important real-world NLG issue, which is software maintenance of NLG systems (bug fixes, adapting to new data sources, supporting changing user needs, etc). I have written some thoughts about this below, there will be more in the book.

Prompt Engineer 111

Prompt Engineer Prompt Engineering Large Language Models LLM 111

IBM Journey to AI blog

OCTOBER 20, 2024

Three years ago, Australia, the UK and the US launched AUKUS, a trilateral security partnership to enhance stability in the Indo-Pacific and beyond. AUKUS is organized around two key pillars: supporting the Royal Australian Navy with nuclear-powered submarines and advancing military technology, such as AI (artificial intelligence), quantum computing and cybersecurity.

Artificial Intelligence 100

Artificial Intelligence Artificial Intelligence Robotics Generative AI 100

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

OCTOBER 20, 2024

Vision-Language-Action Models (VLA) for robotics are trained by combining large language models with vision encoders and then fine-tuning them on various robot datasets; this allows generalization to new instructions, unseen objects, and distribution shifts. However, various real-world robot datasets mostly require human control, which makes scaling difficult.

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Robotics Inference Engine Large Language Models ML 119

Marktechpost

OCTOBER 20, 2024

Large language models (LLMs) have revolutionized the field of artificial intelligence by performing a wide range of tasks across different domains. These models are expected to work seamlessly in multiple languages, solving complex problems while ensuring safety. However, the challenge lies in maintaining safety without compromising performance, especially in multilingual settings.

AI Research 118

AI Research AI Researcher Inference Engine AI 118

Robot Writers AI

OCTOBER 20, 2024

One of the easiest ways to edit text in ChatGPT — once you have a draft that works for you — is to use the AI’s new onboard editor, Canvas. A godsend to writers and editors, Canvas comes equipped with a number of handy tools that enable you to make quick, surgical and artful changes to any text. But easily the most powerful tool of the lot is Canvas’ ‘highlight-and-change’ feature.

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ChatGPT Robotics AI Engineer AI 64

Marktechpost

OCTOBER 20, 2024

A primary feature of sophisticated language models is In-Context Learning (ICL), which allows the model to produce answers based on input instances without being specifically instructed on how to complete the task. In ICL, a few examples that show the intended behavior or pattern are shown to the model, which then applies this knowledge to handle a new query that exhibits the same pattern.

Machine Learning 118

Machine Learning Inference Engine ML Artificial Intelligence 118

Machine Learning Research at Apple

OCTOBER 20, 2024

The growing demand for personalized and private on-device applications highlights the importance of source-free unsupervised domain adaptation (SFDA) methods, especially for time-series data, where individual differences produce large domain shifts. As sensor-embedded mobile devices become ubiquitous, optimizing SFDA methods for parameter utilization and data-sample efficiency in time-series contexts becomes crucial.

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Marktechpost

OCTOBER 20, 2024

Large language models (LLMs) have revolutionized various domains, including code completion, where artificial intelligence predicts and suggests code based on a developer’s previous inputs. This technology significantly enhances productivity, enabling developers to write code faster and with fewer errors. Despite the promise of LLMs, many models struggle with balancing speed and accuracy.

Large Language Models 116

Large Language Models Inference Engine Python Artificial Intelligence 116

Pickl AI

OCTOBER 20, 2024

Summary: Learning Artificial Intelligence involves mastering Python programming, understanding Machine Learning principles, and engaging in practical projects. This structured approach prepares you for a successful career in the rapidly growing AI field. Introduction Artificial Intelligence (AI) is transforming industries worldwide, with applications in healthcare, finance, and technology.

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Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 52

Marktechpost

OCTOBER 20, 2024

The discovery of new materials is crucial to addressing pressing global challenges such as climate change and advancements in next-generation computing. However, existing computational and experimental approaches face significant limitations in efficiently exploring the vast chemical space. While AI has emerged as a powerful tool for materials discovery, the lack of publicly available data and open, pre-trained models has become a major bottleneck.

Neural Network 116

Neural Network Inference Engine AI AI 116

Bugra Akyildiz

OCTOBER 20, 2024

Articles Alibaba announced their Foundation Model series(QWEN) in the following blog post. This is the model versioned 2.5 and it brings the following improvements upon Qwen2: Significantly more knowledge and has greatly improved capabilities in coding and mathematics , thanks to our specialized expert models in these domains. Significant improvements in instruction following , generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs

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Data Scientist LLM Python Algorithm 52

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Business Intelligence

Marktechpost

OCTOBER 20, 2024

One of the most critical challenges of LLMs is how to align these models with human values and preferences, especially in generated texts. Most generated text outputs by models are inaccurate, biased, or potentially harmful—for example, hallucinations. This misalignment limits the potential usage of LLMs in real-world applications across domains such as education, health, and customer support.

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Inference Engine LLM Large Language Models ML 110

TheSequence

OCTOBER 20, 2024

Created Using Ideogram Next Week in The Sequence: You can subscribe to The Sequence below: Edge 441: We are closing our series about SSMs with an exploration of SSMs for non-language modalities. We discuss Meta AI’s research about SSMs for speech recognition and dive into the Llama-Factory framework. Edge 442: We dive into DeepMind’s fascinating AlphaProteo model for protein design.

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OpenAI LLM AI Research AI Researcher 52

Marktechpost

OCTOBER 20, 2024

The growing reliance on large language models for coding support poses a significant problem: how best to assess real-world impact on programmer productivity? Current approaches, such as static bench-marking based on datasets such as HumanEval, measure the correctness of the code but cannot capture the dynamic, human-in-the-loop interaction of real programming activity.

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LLM Inference Engine Large Language Models ML 64

Marktechpost

OCTOBER 20, 2024

In the rapidly evolving world of AI, challenges related to scalability, performance, and accessibility remain central to the efforts of research communities and open-source advocates. Issues such as the computational demands of large-scale models, the lack of diverse model sizes for different use cases, and the need to balance accuracy with efficiency are critical obstacles.

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Large Language Models Inference Engine Natural Language Processing AI Developer 111

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