Category: 3-SometimeTechTalk

In this episode of Leaders of Code, Stack Overflow’s Janice Manningham and Josh Zhang sit down with Cloudflare VP Will Allen to discuss the innovative pay-per-crawl model co-launched by their organizations. They explore how the rise of AI has disrupted the traditional “open versus block” internet model, creating a need for platforms to protect their content and data from commercial exploitation while maintaining community access.

The discussion also:

• Explores the future of the bot ecosystem, emphasizing the importance of putting publishers back in the driver’s seat to decide how their content is accessed and monetized.
• Explains the technical implementation of the pay-per-crawl system, which uses Cloudflare’s bot categorization and WAF rules to serve a 402 “Payment Required” message to specific crawlers.
• Highlights the strategic value of data licensing, comparing comprehensive enterprise contracts with the more flexible, programmatic pay-per-use access enabled by the new model.

Notes

• Connect with Will Allen, Janice Manningham and Josh Zhang on LinkedIn.
• Learn more about Stack Overflow Data Licensing here.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Lila Ibrahim is the COO of Google DeepMind. James Manyika is the senior Vice President for Research, Technology, and Society at Google. The two join Big Technology Podcast to discuss how Google's AI effort operates and runs experiments. In this conversation, we discuss the fundamental operating structure of DeepMind, how Google proper has become more experimental with the revival of Labs and other programs, and how the company is thinking about AI and education. We also cover weather and flood prediction at global scale, and training AI in space. Hit play for a deep inside look at the mechanics behind Google’s AI research machine and the big ideas it’s betting on next.

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Michael Fester grew up in Denmark, the son of a French mother and a Danish father. He was always interested in tech, math and the arts, initially wanting to go into design. However, he did research in number theory at Cambridge, and founded his first startup in Paris, which eventually was acquired by Sonos. Outside of tech, he enjoys reading, in particular the classics - like Dostoyevsky - and biographies - like that of Einstein. He enjoys eating and living healthy, and promotes this lifestyle at his current venture.

Michael and his team noticed that despite the continual improvement of models, the process of maintaining systems using AI was tedious. Not only did this impact support operations, and building software for this area of a business, but negatively impacted the customers themselves. He and his wife wanted to build the new standard for how support operations are run.

This is the creation story of 14.ai.

Sponsors

• Unblocked
• Mezmo
• Braingrid.ai
• Alcor
• Equitybee
• Terms and conditions: Equitybee executes private financing contracts (PFCs) allowing investors a certain claim to ESO upon liquidation event; Could limit your profits. Funding in not guaranteed. PFCs brokered by EquityBee Securities, member FINRA.

Links

• https://14.ai/
• https://www.linkedin.com/in/michaelfester

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Ryan sits down with Shireesh Thota, CVP of Azure Databases at Microsoft, to discuss the evolution of databases at Microsoft; Azure’s comprehensive portfolio that includes SQL Server, CosmosDB, and Postgres; and the challenges that come with database architecture, from the importance of cost governance and multi-cloud strategies to the future of databases when it comes to AI.

Episode notes: 

You can read all about the latest Azure database announcements from Microsoft Ignite—including updates for SQL Server, Postgres, DocumentDB, and Fabric—on their Azure blog. 

Connect with Shireesh on LinkedIn.

Today’s shoutout goes to user Guffa for winning a Populist badge on their answer to Virtual method tables. 

TRANSCRIPT

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We're also joined by Steven Adler, ex-OpenAI safety researcher and author of Clear-Eyed AI on Substack. We cover: 1) The Viral "Something Big Is Happening" essay 2) What the essay got wrong about recursive self-improving AI 3) Where the essay was right about the pace of change 4) Are we ready for the repercussions of fast moving AI? 5) Anthropic's Claude Opus 4.6 model card's risks 6) Do AI models know when they're being tested? 7) An Anthropic researcher leaves and warns "the world is in peril" 8) OpenAI disbands its mission alignment team 9) The risks of AI companionship 10) OpenAI's GPT 4o is mourned on the way out 11) Anthropic raises $30 billion

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Recorded last December at AWS re:Invent, Ryan welcomes CEO and co-founder of Deepgram, Scott Stephenson, for a conversation on advancing voice AI technology. They cover how Deepgram is improving speech-to-text and text-to-speech capabilities using deep learning to take on challenges posed by dialects and noisy environments and the moral and ethical considerations voice AI companies have to make when it comes to voice cloning and synthetic data training. 

Episode notes: 

Deepgram builds accurate, scalable, and affordable large scale voice AI for speech recognition, generation, and AI Agents.

Connect with Scott on LinkedIn, Twitter, or email him at Scott@Deepgram.com

TRANSCRIPT

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Sridhar Ramaswamy is the CEO of Snowflake. Ramaswamy joins Big Technology Podcast to break down the competitive dynamics in the AI race today, drawing from his experience working at Google and competing with it. We also cover the future of software, looking at whether AI will turn established software companies into "dumb backends." In the second half, we discuss “shadow AI” driving enterprise adoption from the bottom up, the risk of becoming a feature in someone else's platform, and why Chinese open-source models might actually be a net positive for the US. Hit play for a sharp, deeply informed conversation about where AI competition, enterprise software, and the future of work are heading.

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Prashanth Tondapu was born and raised in India, now living in New Delhi, the capital there. He claims to be a textbook nerd, loving technology and information. He reads a lot, primarily eastern philosophy and stuff on being enlightened, basically pointing him to skills in accepting reality. He's married with two girls, 9 and 4 years old, along with a Labrador and a German shepherd. He says that having 3 girls in the house means he has 3 supreme leaders.

Prashanth has worked for companies in the past focused on products - companies like McAffee and the Advisor Board Company. Outside of that, he started to build product after product, but no one wanted to buy his product. Eventually, he was tasked to advise a company in product delivery, which then changed everything.

This is the creation story of Innostax.

Sponsors

• Unblocked
• TECH Domains
• Mezmo
• Braingrid.ai
• Alcor
• Equitybee
• Terms and conditions: Equitybee executes private financing contracts (PFCs) allowing investors a certain claim to ESO upon liquidation event; Could limit your profits. Funding in not guaranteed. PFCs brokered by EquityBee Securities, member FINRA.

Links

• https://innostax.com/
• https://www.linkedin.com/in/prashanth-tondapu

Support this podcast at — https://redcircle.com/code-story-insights-from-startup-tech-leaders/donations

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The Gene Simmons of Data Protection: Protegrity's KISS Method

Today, we are releasing our final FINAL episode from our series, entitled The Gene Simmons of Data Protection - the KISS Method, brought to you by none other than Protegrity. Protegrity is AI-powered data security for data consumption, offering fine grain data protection solutions, so you can enable your data security, compliance, sharing and analytics.

Episode Title: Navigating the Future of Data Management: Type Systems, Quantum Computing, and Protegrity's Innovations

In our final-FINAL episode, we are speaking with Ave Gatton, Director of Generative AI. We talk about how AI safety doesn't end with training, it begins with inference. We explore the overlooked frontier of AI security, from prompt-injection, data leakage, and model manipulation. Ave helps to understand how you can build guardrails that operate in real time, and adapt to evolving threats.

Questions

• What are inference-time threats and why are they becoming a critical focus in AI security? 
• How do inference-time risks differ from training-time risks? 
• Why is inference-time protection critical for safe, scalable AI adoption? 
• How do inference-time threats vary across industries? Is there any industry where these attacks are most prevalent? 
• Why are traditional security models insufficient at inference? 
• What is the impact of inference-time breaches on AI adoption? 
• What role does compliance play in shaping inference-time guardrails?
• What practical steps can organizations take to secure inference today? 
• How can businesses balance performance with security when adding guardrails? 

Links

• https://www.protegrity.com/
• https://www.linkedin.com/in/averell-gatton/

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