Melissa explains the importance of giving developers the choice of working with open source or proprietary options, experimenting with flexible application models, and choosing the size of your model according to the use case you have in mind. Discussing the democratization of technology, we explore common challenges in the context of AI including the potential of generative AI versus the challenge of its implementation, where true innovation lies, and what Melissa is most excited about seeing in the future.

Key Points From This Episode:

• An introduction to Melissa Evers, Vice President and General Manager of Strategy and Execution at Intel Corporation.
• More on the communities she has played a leadership role in.
• Why open source governance is not an oxymoron and why it is critical.
• The hard work that goes on behind the scenes at open source.
• What to strive for when building a healthy open source community.
• Intel’s perspective on the importance of open source and open AI.
• Enabling developer choices about open source or proprietary options.
• Growing awareness around building architecture around the freedom of choice.
• Identifying that a model is a bad choice or lacking in accuracy.
• Thinking critically about future-proofing yourself with regard to model choice.
• Opportunities for large and smaller models.
• Finding the perfect intersection between value delivery, value creation, and cost.
• Common challenges in the context of AI, including the potential of generative AI and its implementation.
• Why there is such a commonality of use cases in the realm of generative AI.
• Where true innovation and value lies even though there may be commonality in use cases.
• Examples of creative uses of generative AI; retail, compound AI systems, manufacturing, and more.
• Understanding that innovation in this area is still in its early development stages.
• How Wardley Mapping can support an understanding of scale.
• What she is most excited about for the future of AI: Rapid learning in healthcare.

Quotes:

“One of the things that is true about software in general is that the role that open source plays within the ecosystem has dramatically shifted and accelerated technology development at large.” — @melisevers [0:03:02]

“It’s important for all citizens of the open source community, corporate or not, to understand and own their responsibilities with regard to the hard work of driving the technology forward.” — @melisevers [0:05:18]

“We believe that innovation is best served when folks have the tools at their disposal on which to innovate.” — @melisevers [0:09:38]

“I think the focus for open source broadly should be on the elements that are going to be commodified.” — @melisevers [0:25:04]

Links Mentioned in Today’s Episode:

Melissa Evers on LinkedIn

Melissa Evers on X

Intel Corporation

VP of AI and ML at Synopsys, Thomas Andersen joins us to discuss designing AI chips. Tuning in, you’ll hear all about our guest’s illustrious career, how he became interested in technology, tech in East Germany, what it was like growing up there, and so much more! We delve into his company, Synopsys, and the chips they build before discussing his role in building algorithms.

Key Points From This Episode:

• A warm welcome to today’s guest, Thomas Andersen.
• How he got into the tech world and his experience growing up in East Germany.
• The cost of Compute AI coming down at the same time the demand is going up.
• Thomas tells us about Synopsys and what goes into building their chips.
• Other traditional software companies that are now designing their own AI chips.
• What Thomas’ role looks like in machine learning and building AI algorithms.
• How the constantly changing rules of AI chip design continue to create new obstacles.
• Thomas tells us how they use reinforcement learning in their processes.
• The different applications for generative AI and why it needs good input data.
• Thomas’ advice for anyone wanting to get into the world of AI.

Quotes:

“It’s not really the technology that makes life great, it’s how you use it, and what you make of it.” — Thomas Andersen [0:07:31]

“There is, of course, a lot of opportunities to use AI in chip design.” — Thomas Andersen [0:25:39]

“Be bold, try as many new things [as you can, and] make sure you use the right approach for the right tasks.” — Thomas Andersen [0:40:09]

Links Mentioned in Today’s Episode:

Thomas Andersen on LinkedIn

Synopsys

How AI Happens

Sama

Developing AI and generative AI initiatives demands significant investment, and without delivering on customer satisfaction, these costs can be tough to justify. Today, SVP of Engineering and General Manager of Xactly India, Kandarp Desai joins us to discuss Xactly's AI initiatives and why customer satisfaction remains their top priority.
Key Points From This Episode:

• An introduction to Kandarp and his transition from hardware to software.
• How he became SVP of Engineering and General Manager of Xactly India.
• His move to Bangalore and the expansion of Xactly’s presence in India.
• The rapid modernization of India as a key factor in Xactly’s growth strategy.
• An overview of Xactly’s AI and generative AI initiatives.
• Insight into the development of Xactly’s AI Copilot.
• Four key stakeholders served by the Xactly AI Copilot.
• The Xactly Extend, an enterprise platform for building custom apps.
• Challenges in justifying the ROI of AI initiatives.
• Why customer satisfaction and business outcomes are essential.
• How AI is overhyped in the short term and underhyped in the long term.
• The difficulties in quantifying the value of AI.
• Kandarp’s career advice to AI practitioners, from taking risks to networking.

Quotes:

“[Generative AI] is only useful if it drives higher customer satisfaction. Otherwise, it doesn't matter.” — Kandarp Desai [0:11:36]

“Justifying the ROI of anything is hard – If you can tie any new invention back to its ROI in customer satisfaction, that can drive an easy sell across an organization.” — Kandarp Desai [0:15:35]

“The whole AI trend is overhyped in the short term and underhyped long term. [It’s experienced an] oversell recently, and people are still trying to figure it out.” — Kandarp Desai [0:20:48]

Links Mentioned in Today’s Episode:

Kandarp Desai on LinkedIn

Xactly

How AI Happens

Sama