Deep Takes Not Fakes Adam Granoff, Dave Castellani

How can we integrate AI into an organization’s overall strategy to maximize its benefits? In this episode, we continue our deeper takes conversations with guest host Nishit Sadhwani, Corporate Vice President at New York Life Insurance Company, to discuss how the rapid development of generative AI is impacting businesses and the role of CIOs and entrepreneurs in driving innovation. We unpack how AI is disrupting the business landscape – from start-ups to large enterprise organizations – and its impact on innovation, competition and organizational structure, before taking a closer look at how to embrace AI tools for enhanced productivity. Our conversation also investigates the entrepreneurial opportunities created by AI, why larger companies should consider strategic partnerships with startups to accelerate innovation, and much more. For a deep dive into our perspectives on driving innovation and how CIOs and entrepreneurs should be integrating AI for maximum benefit, be sure to tune in!
 
Key Points From This Episode:
How CIOs should approach AI integration for maximum benefits. CIOs' leadership role in demystifying technology for business use. How AI democratizes power and empowers individuals. An overview of the entrepreneurial opportunities created by AI. Challenges that entrepreneurs are going to face in the new world of AI. Ways that AI will generate faster innovation and greater competition. Why disruption is inevitable: the importance of businesses’ willingness to pivot. Adapting business models to leverage AI technologies and stay competitive. How organizations need to rethink their partnerships. Expected radical changes in how tech organizations are structured due to AI. AI’s impact on the workforce, collaboration, and automation. Embracing AI tools to enhance productivity and stay ahead of the competition.  
Links Mentioned in Today’s Episode:
Nishit Sadhwani on LinkedIn
Nishit Sadhwani on X
New York Life Insurance Company
Episode – Deeper Takes 1 with Nishit Sadhwani: Balancing Innovation and Risk
Episode – Deeper Takes 2 with Nishit Sadhwani: Unlocking the Power of Data
Elon Musk
Adam Granoff on LinkedIn
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X

Ever wondered what it takes to navigate the dynamic world of tech investing? In this episode, we sit down with Maria Palma to unpack tech investing, AI, and crypto. Maria is a seasoned investor and business leader with a diverse background spanning venture capital, entrepreneurship, and engineering. As a General Partner at Kindred Capital, Maria plays a role in shaping the technology landscape. Kindred Capital is not just a venture capital firm; it's a community of visionaries, innovators, and trailblazers. With a focus on technology and entrepreneurship, Kindred Capital is dedicated to nurturing innovation and driving meaningful change in the startup ecosystem. In our conversation, we explore why companies are hesitant to embrace AI and the advantages it offers both startups and larger enterprises. Dive deep into whether AI will render software developers obsolete and uncover the nuances between regulated and unregulated cryptocurrencies. Maria also talks about the potential intersection of AI and crypto, navigating the technology hype-cycle, the technology sectors she is investing in, the best use cases of AI for enterprise, and much more! Join us as we delve into the dynamic world of technology investing, AI, and cryptocurrency through the lens of a veteran investor, Maria Palma!
 
Key Points From This Episode:
Background about Maria and her passion for technology.
What she thinks is the most exciting technology to investors.
Her approach to identifying what AI-based technology is investable.
Examples of the type of companies she has invested in.
Ways AI is shaking up the enterprise and investment landscape.
The six areas of AI she is focusing her investment efforts on.
AI code generation and its role in software development.
Cryptocurrencies and why people should be paying attention to them.
Discover the potential intersection of AI and cryptocurrencies.
Why understanding a company’s problems is essential for AI adoption.
Reasons why she finds small and medium-sized businesses compelling.
Maria shares advice for budding crypto investors.
 
Links Mentioned in Today’s Episode:
Maria Palma on LinkedIn
Kindred Capital
Adam Granoff on LinkedIn
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X

As we continue to explore the aftermath of the tidal wave that is AI, we are reminded of the challenges that can be found in the wake of the generative AI and large language model explosion. But there are also countless opportunities for innovation and growth, and that is where today’s guest comes in. John Sapone is the Senior Vice President of Sales at Snowflake – a cloud data platform that is secure, governed, and infinitely scalable – and he explains how his time at ServiceNow helps him in his current role at Snowflake. We discuss the state of data today, how John and his team coach organizations in the best practices for data management, and what Snowflake as a company is all about. John walks us through the biggest opportunities that lie ahead for his company, how he and his team breed success, how AI has reshaped business at Snowflake, and how the company aims to solve the mistakes that many organizations are still making around data and AI. We end with John’s advice for business leaders on how to use data and AI effectively and responsibly. 
 
Key Points From This Episode:
John Sapone walks us through his background and what he enjoys doing in his downtime. 
What he learned during his time at ServiceNow and how it applies to his work at Snowflake.
The state of data today, and how he helps companies to evaluate and utilize data efficiently. 
Exploring the ins and outs of Snowflake and what the company aims to achieve. 
The biggest opportunities that await Snowflake in the next 3-5 years. 
Patterns of success that John and his team have awakened at Snowflake
How Snowflake has changed since the explosion of generative AI. 
The way AI altered Snowflake’s approach to market. 
Pitfalls and common mistakes that organizations make that Snowflake can help solve.
John’s advice to business leaders on how to use AI responsibly and the best practices for data management.  
 
Links Mentioned in Today’s Episode:
John Sapone on LinkedIn 
Snowflake 
ServiceNow 
Frank Slootman on LinkedIn 
Nimble Storage 
Snowflake Cortex for Generative AI 
Adam Granoff on LinkedIn 
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X

Large language models, generative AI – all of it is moving at such blinding speed that it’s difficult to stay on top of the latest developments. As such, we’ve decided that regular check-ins on the state of generative AI is now a necessity rather than a preference so today, we’ve invited Dan Giannone back onto the show to walk us through the current trends he’s seeing in generative AI. Dan is the Cloud Solutions Architect at Microsoft, and after walking us through what his role entails, he explains why consumers don’t know enough about cloud services and what can be done to educate them. Our discussion then turns to the rapid evolution of generative AI, how Dan and his team are keeping customers up-to-date about new innovations, why business leaders need to be less cynical about the big data revolution, how understanding AI is a process and not instant, and how to know when your business is ready to introduce LLMs to its systems. We also discuss what’s missing from the generative AI playbook, the importance of building AI-centered teams, the value of solutions accelerators, and why AI hallucinations shouldn’t be a major concern for businesses. To understand the customer’s role in the effective use of AI, the biggest myths about AI, and how leading technology companies are grappling with the LMM disruption, press play now.     
 
Key Points From This Episode:
Dan Giannone’s professional background and what his current role at Microsoft entails. A day in the life of a cloud solutions architect.  Why there’s a need to better educate consumers on the finer details of cloud services.  The (rapid) evolution of generative AI, and how Dan explains new innovations to customers. Assessing the big data revolution and why business leaders need to be less cynical about it.  How using and understanding generative AI is a patient process of collaboration and agility. The balance between adopting LLMs early and ensuring that your business is ready for it. Searching for the missing playbook, and how to build successful AI-centered teams.  How solution accelerators can facilitate faster growth.   Understanding one of generative AI’s biggest drawbacks: hallucinations.   The role of consumers in the effective use of generative AI. Talking through some of the biggest mistakes and misconceptions that users have of AI.  How big technology leaders are coping (or not coping) with the LMM disruption.   
Links Mentioned in Today’s Episode:
Dan Giannone on LinkedIn
Microsoft 
Microsoft Copilot
‘My First RAG Use-Case - Key Insights & Lessons Learned’ 
‘Chat with Your Data’ Solution Accelerator 
ChatGPT 
Perplexity AI
Adam Granoff on LinkedIn
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X

Unlocking the potential of data for AI is akin to discovering the hidden keys to a treasure trove of knowledge. Data serves as the foundation on which AI thrives and evolves. However, not just any data will do. It is the quality of this information that holds the real power. In this episode, we follow on from our deeper takes episode with guest host Nishit Sadhwani, Corporate Vice President at New York Life Insurance Company, to explore the intricate world of data management in AI; unpacking its challenges, nuances, and transformative potential. In our conversation, we discuss the critical challenges that organizations face in handling data for AI development, why data reliability and quality are vital, and the importance of not just the data itself but also the teams that manage it. Gain insights into the governance issues surrounding data management, the steps organizations can take to ensure data integrity, the concept of “destiny data”, and much more. We also discuss the critical intersection of data quality, AI development, and user privacy in today’s ever-evolving tech landscape. To find out how to unlock the potential of data to give your organization the competitive edge it needs, tune in now!
 
Key Points From This Episode:
Challenges organizations face regarding data management in AI.
Why good, reliable data is essential to unlocking AI’s potential.
The concept of a ‘data mesh’ and sharing data effectively.
Discover why the team is just as valuable as data.
Adapting data solutions to fit the structure of the organization.
Insights into data management governance issues.
What organizations can do to ensure the integrity of data.
Data quality and how it impacts AI development.
Ensuring user privacy while enhancing AI capabilities.
How AI can be leveraged to solve user privacy problems.
Leveraging existing data with AI to gain a competitive advantage.
Final takeaways and words of advice for listeners.
 
Links Mentioned in Today’s Episode:
Nishit Sadhwani on LinkedIn
Nishit Sadhwani on X
New York Life Insurance Company
Episode – Deeper Takes 1 with Nishit Sadhwani: Balancing Innovation and Risk
Episode – Bill White On Destiny Data & Its Impacts on Business and Technology Strategy
Episode – AI and Its Impact on Business with John de Havilland
Copilot for Microsoft 365 
Adam Granoff on LinkedIn
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X

During this episode, Jeff Kauflin, journalist at Forbes, joins us to share his perspective on the areas he covers. Tuning in, you’ll hear Jeff define the basic concepts of bitcoin and ethereum, along with his predictions on how each will continue to evolve. We explore how Jeff chooses which companies to highlight and some of the metrics he uses to predict their future growth. This episode also discusses the influence and potential threat of AI to fintech and journalism, and what may happen to NFTs in the future. Listeners will also hear Jeff’s perspective on how AI could facilitate financial fraud and how best to protect yourself and your company from the risks it poses. Tune in for a value-packed episode filled with essential insights from today’s expert guest. 
 
Key Points From This Episode:
Introducing Jeff Kauflin, journalist at Forbes. 
His deserted island books including Michener, Ralph Waldo Emerson, and the New Yorker.
His role at Forbes, reporting on fintech and crypto. 
The challenge of drawing out key stories in the fintech and crypto space including personal finance and insure tech. 
Factors that set companies apart to introduce to readers.
Why the impact of AI on fintech is slower than expected.
How fintech is using generative AI. 
Why Jeff doesn’t see AI as a threat to the industry. 
How AI could create efficiencies for journalists. 
How Jeff would set about to explain exactly what bitcoin and ethereum is to a beginner.
His predictions on how this industry will continue to evolve.
What he expects from the future of NFTs.
The impact of AI on financial fraud.
How to protect yourself and your company from the risk of financial fraud.
 
Links Mentioned in Today’s Episode:
Jeff Kauflin on LinkedIn
Jeff Kauflin Blog
Jeff Kauflin on X
James Michener on Amazon
Ralph Waldo Emerson on Amazon
The New Yorker
The Fintech 50
April Tax
Column Tax
How AI is Supercharging Financial Fraud and Making it Harder to Spot
Adam Granoff on LinkedIn
Dave Castellani on LinkedIn
Deep Takes, Not Fakes
Deep Takes, Not Fakes on Instagram
Deep Takes, Not Fakes on Facebook
Deep Takes, Not Fakes on X