This Week's Most Read: Developing an 'AI IQ' for Business Success

An opinion piece from IBM's former CAIO, a primer on generative AI and a new $1 billion 'supercloud'

Deborah Yao, Editor

October 5, 2023

3 Min Read

Here are this week's most popular stories:

1. Developing an 'AI IQ' for Business Success

Artificial intelligence (AI) holds tremendous promise. Yet, most companies have to work hard to capture its benefits. While data science and machine learning were hyped in the 2010s, fewer than 25% of firms adopted more than one AI model. Now, generative AI like ChatGPT is the hot new trend. For some reason, they believe they will succeed with generative AI using the same approaches. However, companies need to change their approach to avoid repeating past disappointments.

The solution lies in a proven methodology aligning AI to business strategy across people, processes, and technology using a human-focused and value-based approach. Here, IBM's former global CAIO - now founder of Qantm AI - outlines a practical roadmap so organizations can leverage AI to achieve strategic goals from the C-suite to frontline operations.

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2. What is Generative AI and How is it Different from Other AI?

2023 will go down as the year when generative AI went mainstream, with applications like ChatGPT, Google Bard, DALL-E and Midjourney grabbing headlines for their startling ability to create prose and art from just a simple text prompt.

These are all examples of generative AI — artificial intelligence which can create new content on the fly. But what is generative AI and how does it work? Unlike other forms of AI — for example, algorithms designed to look for patterns and make predictions — generative AI is defined by its ability to produce new and original work of its own.

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3. New $1 Billion ‘AI Supercloud’ to Power Business AI Workloads

U.K.-based NexGen Cloud is gearing up to launch an ‘AI Supercloud’ service to power high-performance computing for AI applications.

The project is designed to meet the increasing demand for computing resources amid the generative AI wave. NexGen’s Supercloud platform aims to offer cost-effective access to GPU cloud services for European businesses and startups.

The company plans to invest $1 billion in the project – with some $576 million already earmarked for hardware from suppliers.

Among the hardware set to power the Supercloud will be more than 20,000 H100 GPUs from Nvidia, which are expected to arrive by June 2024. Access to the AI Supercloud will be provided via NexGen’s recently announced Hyperstack platform, a GPU-accelerated cloud platform powered by Nvidia tech that enables direct-to-compute, GPU-accelerated cloud access for the European market.

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4. Zuckerberg Philanthropy to Use AI to 'Cure, Prevent or Manage All Disease'

Mark Zuckerberg is betting big on AI to cure diseases.

The Chan Zuckerberg Initiative (CZI), the Meta CEO’s philanthropic arm co-chaired by his wife Priscilla Chan, is planning to build what it describes as one of the largest computing systems in the world dedicated to nonprofit life science research.

The high-performance computing cluster expects to house more than 1,000 GPUs designed for AI and large language models (LLMs). The project will offer scientists access to predictive models for both healthy and pathological cells in the hope of making medical breakthroughs.

“Building this AI computing system is a crucial step towards curing, preventing, or managing all diseases by the end of the century because it will deepen the scientific community’s understanding of cells and how cells interact within systems,” Patricia Brennan, vice president of Science Technology at the initiative, said in an interview.

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5. Meta's Llama 2 Long: Longer Memory, Handles Heftier Tasks

Meta has upgraded its flagship open-source Llama 2 large language model to improve its ability to handle lengthier inputs.

Researchers unveiled Llama 2 Long in a paper, contending it is on par with proprietary models that have longer context windows such as Claude 2 from Anthropic, while remaining open source.

Llama 2 Long can handle texts up to 32,768 tokens – with larger versions of the model able to deal with contexts more effectively. The upgraded model surpasses the original version on both long context tasks like summarization, question-answering and aggregation as well as on standard short-context benchmarks.

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About the Author(s)

Deborah Yao

Editor

Deborah Yao runs the day-to-day operations of AI Business. She is a Stanford grad who has worked at Amazon, Wharton School and Associated Press.

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