Sun.Oct 20, 2024

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Structuring Inputs and Outputs in Multi-agent systems Using CrewAI

Analytics Vidhya

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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Partners are the linchpin for scaling enterprise AI success

IBM Journey to AI blog

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

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Maintaining NLG Systems

Ehud Reiter

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.

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How technology and information sharing can help AUKUS protect the Indo-Pacific

IBM Journey to AI blog

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.

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

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

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Latent Action Pretraining for General Action models (LAPA): An Unsupervised Method for Pretraining Vision-Language-Action (VLA) Models without Ground-Truth Robot Action Labels

Marktechpost

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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This AI Research from Cohere for AI Compares Merging vs Data Mixing as a Recipe for Building High-Performant Aligned LLMs

Marktechpost

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.

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ULTIMATE GUIDE:  New ChatGPT Editor, Canvas

Robot Writers AI

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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This Machine Learning Research Discusses How Task Diversity Shortens the In-Context Learning (ICL) Plateau

Marktechpost

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.

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Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement

Machine Learning Research at Apple

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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15 Modern Use Cases for Enterprise Business Intelligence

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?

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aiXcoder-7B: A Lightweight and Efficient Large Language Model Offering High Accuracy in Code Completion Across Multiple Languages and Benchmarks

Marktechpost

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.

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How to Learn Artificial Intelligence From Scratch in 2024?

Pickl AI

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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Meta AI Releases Meta’s Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Marktechpost

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.

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Alibaba Foundation Models: QWEN Series

Bugra Akyildiz

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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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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CREAM: A New Self-Rewarding Method that Allows the Model to Learn more Selectively and Emphasize on Reliable Preference Data

Marktechpost

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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NVIDIA Releases Nemotron 70B

TheSequence

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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RealHumanEval: A Web Interface to Measure the Ability of LLMs to Assist Programmers

Marktechpost

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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Open Collective Releases Magnum/v4 Series Models From 9B to 123B Parameters

Marktechpost

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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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

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.