Friday, November 22, 2024
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Hi, it’s Chad. Welcome to the Friday edition of your Leadership Inspiration. Every Friday, I serve as your AI guide to help you navigate a rapidly evolving landscape, discern signals from noise and transform cutting-edge insights into practical leadership wisdom. If you’d like me to work with your team or speak at an event in 2025, please get in touch asap. The first quarter of the year is always busy for me. And now, on to the content. Here’s what you need to know:
1. Algorithmic Musings: The Evolution of AI Research.
Over the past several months I’ve dialed back my blog postings in favor of crafting articles and analyses for our AI for the C Suite subscribers. Yet this week I published a new blog post offering insight into the rapidly maturing field of AI. Check out my post The Evolution of AI Research: Analyzing arXiv Submission trends (2019-2024).
2. Paper Trail: AI Research Decoded
Assessing and Understanding the Prompt Sensitivity of LLMs
Larger language models show improved prompt robustness, with few-shot examples significantly enhancing their reliability across diverse tasks. Here are the key takeaways:
- Model size correlates with prompt robustness: Larger models like Llama3-70B-Instruct demonstrate exceptional stability in responses across different prompting styles
- Few-shot examples dramatically improve performance: Even one example significantly reduces prompt sensitivity, with larger models showing greater benefits from additional examples
- Task-specific sensitivity patterns emerge: LLMs show higher robustness in knowledge-based tasks but increased sensitivity in creative and coding tasks
AI Computer Agents: Hands “Off” with Claude Computer Use
New research goes deep with Claude’s ‘Computer Use’ beta tool to reveal practical pathways for middle market organizations to implement AI computer automation while minimizing risks and maximizing returns. Here’s the high level overview:
- AI computer agents can effectively handle routine tasks with 80% success rate, offering immediate cost-saving opportunities
- Implementation success depends on strategic phasing, clear processes, and appropriate human oversight
- Technology maturity suggests a 3-phase adoption approach over 2-3 years for optimal results
Read our full analysis of each of these research papers at AI for the C Suite
3. Sound Waves: Podcast Highlights
Just in time to serve as a side with your Thanksgiving turkey, our next podcast episode drops Monday, November 25th. Listen in as I talk AI with Cameron Duncan of Hallian Technologies. Check it out and Subscribe for free today on your listening platform of choice to ensure you never miss a beat.
New episodes release every two weeks.
4. Digital Dojo
Over the past sixty (60) days I’ve noticed an important evolution with the way AI tools respond to conversations regarding their errors. For example, it’s no longer always as efficient to granularly lead the AI system through its error. Instead, I now ask it to specifically assess the area where I’ve identified a problem. This is a distinctly different approach than the oft-recommended Chain of Thought prompting.
The technique I’m describing proves especially helpful when working with images. For example, when working with Claude this week I identified an error where text was formatted improperly within an infographic. I then asked Claude “Do you see the error with the text formatting within the Phase 1 and Phase 3 boxes?” Claude then replied “Yes, I notice the text in Phase 1 and Phase 3 boxes extends beyond the boundaries of their respective boxes, making it difficult to read. Let me fix the text wrapping and spacing to ensure all content fits properly within the defined boundaries.”
The conversation I outlined above would not have worked in August – or even September 2024. Yet now it consistently works quite well to deliver the desired result. In my opinion, this is an example of both the increased capability of the system but also, perhaps, an early indicator of the purported new models that are waiting in the wings.
5. Code & Law
In June 2024, a former senior researcher from Open AI, Leopold Aschenbrenner, penned an essay titled “Situational Awareness.” One of the points he made that grabbed my immediate attention was this statement:
As the race to AGI intensifies, the national security state will get involved. The USG will wake from its slumber, and by 27/28 we’ll get some form of government AGI project. No startup can handle superintelligence. Somewhere in a SCIF, the endgame will be on.
Aschenbrenner’s essay informed my thinking about AI and AGI over the past five (5) months. Since then I’ve been on high alert for any news lending credence to his prediction that by 2027-2028 the U. S. government will fund a Manhattan Project-styled-initiative to develop Super Artificial General Intelligence. Then, this past week, I saw this article This Week in AI: Congressional commission warns of Chinese AGI. Confirmation received.
6. Elevate Your Leadership with AI for the C Suite
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Stay safe. Stay healthy. Be strong. Lead well.
Chad