MI&S Weekly Analyst Insights — Week Ending September 20, 2024
by Patrick Moorhead, Bill Curtis, Will Townsend, Melody Brue, Robert Kramer, Matt Kimball, Jason Andersen, Paul Smith-Goodson and Anshel Sag via Moor Insights & Strategy ([Global] Quantum Computing)
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The Moor Insights & Strategy team hopes you had a great weekend!
This week, Patrick, Anshel, and Melody (virtually) will be in Palo Alto at HP Imagine, Anshel will also be in San Jose at Meta Connect in San Jose, and Melody will be at Verint Engage in Orlando.
Last week, Anshel attended the Snap Partner Summit in Santa Monica and Patrick, Jason, Melody, and Robert attended Salesforce Dreamforce in San Francisco (and virtually).
If you missed Will Townsend’s webinar with Zayo, “What’s Next for Your Network’s Foundation?” It is now available on demand!
Our MI&S team published 16 deliverables:
6 Forbes Articles
1 MI&S Research Paper
1 MI&S Research Note
5 MI&S Blog Posts
3 Podcasts
Over the last week, our analysts have been quoted multiple times in top-tier international publications with our thoughts on Apple, IBM, Intel, and Nokia.
Patrick was on Yahoo! Finance with the Morning Brief team to talk about Intel’s AI chipmaking partnerships, and joined CNBC to discuss recent reports that Qualcomm approached Intel about a takeover.
MI&S Quick Insights
Artificial Intelligence (AI) (Paul Smith-Goodson)
Microsoft, BlackRock, Global Infrastructure Partners, and MGX have partnered to raise $100 billion to build AI infrastructure; the group will invest in datacenters and energy infrastructure to support demand for AI computing power, primarily in the United States. The group’s initial objective is to raise $30 billion, with long-term expectations of expanding it to $100 billion with additional debt financing. The partnership’s main focus will be on datacenters and the power supply needed to run giant AI applications.
A group of Chinese researchers published a paper exploring memory in large language models. The scientists believe that LLMs have a unique type of memory similar to Schrödinger’s cat. The memory can only be observed when a question is asked. The universal approximation theorem (UAT) was used to explain how LLMs can dynamically fit inputs to outputs, making it appear to remember information.
Experiments were run on LLMs by training them on poems, then testing the LLM’s ability to recall the poems based on very little information. It surprised me that the LLMs could remember entire poems based only on titles and authors, even though LLMs don’t store information in a traditional memory structure. The scientists wrapped up the experiment by comparing LLM memory to human cognition. They highlighted similarities and differences and emphasized the potential of the dynamic fitting capability for creativity and innovation.
Artificial Intelligence (AI) (Paul Smith-Goodson)
Microsoft, BlackRock, Global...
Check out the vacancies at: https://www.graphcore.ai/jobs