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In an era where artificial intelligence is reshaping industries and driving unprecedented innovation, staying ahead of the curve is more important than ever. At NexaQuanta, we’re dedicated to providing you with the latest breakthroughs, expert analysis, and impactful AI and machine learning updates.
This edition highlights cutting-edge advancements in generative AI, foundation models, and automated feedback systems, transforming how enterprises approach technology adoption. From IBM’s powerful updates to watsonx.ai to the launch of hyperrealistic AI image-generation tools, this newsletter is packed with developments you can’t afford to miss.
Stay ahead, stay informed, and let AI drive your next big move.
Red Hat and IBM Launch RHEL AI Platform with InstructLab
Red Hat and IBM have collaborated to launch the RHEL AI platform, which aims to simplify the development, testing, and deployment of generative AI models. This platform seeks to make large language models (LLMs) as accessible as open-source software, reducing the complexity and cost of using these advanced AI systems.
InstructLab: A Community-Driven Approach
The InstructLab project, led by IBM and Red Hat, introduces a new method for working with LLMs through community contributions. Regardless of technical expertise, users can contribute skills and knowledge to the model. This approach is designed to lower costs, remove barriers to experimentation, and improve the accuracy and alignment of AI models with user values.
Benefits of InstructLab
InstructLab offers several advantages, including:
- Cost-effectiveness: The project’s open-source nature makes it accessible to anyone with basic hardware, such as a laptop. Community-driven instruction tuning reduces the cost of training and developing models.
- Community Involvement: InstructLab encourages a wide range of expertise and perspectives to enhance AI models by involving contributors from diverse fields, including non-technical areas.
- Ease of Use: The platform is user-friendly, allowing even non-technical individuals to contribute by using simple question-and-answer templates.
Contributions can be made through GitHub, and models are regularly updated on platforms like HuggingFace. This initiative aims to democratise access to AI, ensuring more inclusive and collaborative development in generative AI.
Check further details here.
IBM Updates Watsonx.ai with Custom Foundation Model Capabilities
IBM has introduced a new feature update to its watsonx.ai platform, allowing users to upload and deploy custom foundation models across software and SaaS environments. This new open framework provides access to a catalogue of built-in models and patterns, giving businesses greater flexibility to meet their specific generative AI use cases.
Custom Foundation Models for Tailored AI Solutions
Since its launch in July 2023, IBM’s watsonx.ai AI studio has enabled companies to train, validate, and deploy AI models. The latest update expands this functionality by allowing users to import custom foundation models. It addresses unique business needs such as industry-specific tasks or specialised language support.
For example, businesses can now deploy models fine-tuned for their industry or specific tasks like summarising customer service transcripts or generating personalised emails. This flexibility empowers users to optimise AI models according to their domain-specific requirements.
Supported Model Types
The platform supports several model architecture types: bloom, falcon, gpt_neox, llama2, and more. Custom models can be imported and deployed for natural language and programming language generation tasks, though further tuning of custom models is not yet available.
Enhanced Governance and Integration
Deployed models benefit from watsonx.ai’s enterprise-level governance features, ensuring safe and reliable use. With both SaaS and on-premises options, users can bring their custom models closer to their data, minimising risks and improving efficiency.
This update underscores IBM’s commitment to making AI development more flexible and accessible for businesses, allowing for deeper customisation and better alignment with specific goals.
Open this link for more details.
Llama 3.1 Models Now Available on IBM Watsonx.ai
Meta has announced the release of the Llama 3.1 collection of large multilingual language models (LLMs). It is now available on IBM’s Watsonx.ai platform. This update brings enhanced features and capabilities, providing more flexibility for developers working with generative AI.
Key Features of Llama 3.1:
- Multilingual Support: Llama 3.1 now accommodates a wider range of languages, broadening its applicability in diverse linguistic contexts.
- Function Calling: The new models support function calling, enabling more efficient handling of complex AI tasks.
- Extended Context Length: Llama 3.1’s context length is increased to 128k tokens, allowing for more detailed and nuanced AI responses.
These updates make Llama 3.1 an attractive option for businesses leveraging AI for multilingual tasks and complex use cases.
Read details here.
New AI Image Generators Like FLUX.1 Are Raising Concerns About Hyperrealism and Misuse
This summer, several advanced artificial intelligence tools capable of creating hyperrealistic photos released, making it increasingly challenging for consumers to distinguish between real and AI-generated images. Among the most powerful of these new tools is FLUX.1, or Flux, a free AI image generator released in August. Flux allows users to create hyperrealistic images without a subscription.
What is Flux? Flux can generate convincing images of people and recognisable locations in seconds. Unlike other AI tools, the results lack typical indicators of AI-generated content, such as unnaturally smooth skin. It draws upon thousands of reference images and can produce detailed visuals from simple descriptive prompts.
Concerns Surrounding Flux Although Flux offers powerful capabilities, experts warn of potential misuse. Its open-source nature allows users to modify and use the tool offline, making it difficult to regulate. Despite its terms of service prohibiting deceptive use or copyright violations, concerns remain about the potential for abuse in creating misleading or unlawful content.
As the race to develop hyperrealistic AI tools continues, companies like Black Forest Labs, the creator of Flux, are already planning to expand into video generation, signalling the next frontier in generative AI innovation.
For details, visit this page.
AutoToS: Automated Feedback Enhances Accuracy in AI-Generated Planning Components
Researchers at Cornell University and IBM have developed AutoToS. It is a new system designed to enhance the accuracy of AI-generated planning components. AutoToS generates precise successor and goal test functions for complex AI planning problems.
Perfect Accuracy in Complex Domains AutoToS has demonstrated perfect accuracy in well-known domains like BlocksWorld and Sokoban. It achieved these results with minimal iterations and without human refinement.
Improved AI Planning with Automated Feedback Experiments has shown that applying soundness and completeness tests boosts the quality of planning components across various large language models. This innovation marks a significant step forward in AI-driven planning, providing more reliable and efficient solutions for various applications.
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As AI continues to evolve rapidly, it’s crucial to stay informed about the latest trends and opportunities in the industry. At NexaQuanta, we bring you the most relevant insights and expert analysis to help you leverage AI for your business.
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