In this episode we discuss, 

• The intersection of technology & medicine? 
• How  the medical field, and cardiology in particular has adapted to tech & AI advancements 
• Case-studies revealing the effectiveness of AI techniques
• Whether  medical systems need to change in order to optimize processes and provide better experiences & outcomes for their patients
• Hidden opportunities for entrepreneurs & healthcare practitioners 
• The future of medicine in an AI world

Resources: 

• Books:
• Rebooting AI: Building Artificial Intelligence We Can Trust - Gary Marcus
• The Patient Will See You Now: The Future of Medicine Is in Your Hands -  Eric Topol MD

Ways to follow along with Dr. Anuj, 

• Twitter 
• LinkedIn
• Website

In this episode we discuss,

• The Rise of Fintech - how/when the word "Fintech" became popularized
• If & how AI & Machine learning capabilities has changed the fintech investment landscape
• How startups are leveraging AI to compete and optimize the finance industry. Companies discussed include, Kasisto, HyperScience, Pymetrics, and Theta Lake.
• What regulators and corporate executives at banks like JP Morgan, City Bank, & Master Card look for when working with early stage startups
• How big tech companies like Apple, Facebook, and Google will affect the future of finance
• The Fintech Innovation Lab advantage. If you are an early stage company interested in the program, learn how to apply here.

Ways to connect with Sunny,

• Twitter
• LinkedIn
• Fintech Innovation Lab Website

We discuss,

• The state of Agriculture Technology (Agtech)
• The birth of EIO Diagnostics
• How EIO is leveraging AI to help farmers in the global dairy industry save $10B
• How to train machine learning models for a unique problem set
• How is the industry evolving and what new technologies are farmers and agriculture stakeholders using to optimize processes.
• How are great food/bev products created? What differentiates brands from one another?
• Whether AI makes startups more or less competitive?
• Benefits of startup programs like Food-X

Follow EIO on

• Twitter
• LinkedIn
• Website

*We discuss, *

• How AI generated Art is created (it's harder than you think)
• How to train an AI model to produce results you seek
• How does technology affect the future of art, especially if the art can be generated rather easily?
• How startups can compete in an Ai world
• Practical applications of enterprise & consumer data
• How that data is leveraged for the benefits of businesses and consumers.
• Threats that arise due to a data explosion

*Educational References: *

Blogs & Books:

• Distill Pub
• Open Ai’s blog
• Fair Ai blog
• Google’s Ai blog
• Deep Learning book by Ian Goodfellow and Yoshua Bengio and Aaron Courville

Big thank you to Sunny Parikh for making the connection to Paul and making the podcast possible. 

We discuss,

• What type of AI is being applied to Sports Betting?
  What are the consequences of technology in the gaming industry?
• How both customers and business owners benefit from implementing predictive and real-time gaming tech.
• Five applications of machine learning in the gaming industry, including odds making, risk management, responsible gaming, and more.
• The alignment of incentives when building powerful tech
• The role of society, government, and corporations in the creation and regulation of AI and deep technologies like it.

Resources discussed,

• Great machine learning courses - [Khan Academy]or [Coursera]
• Going deep on AI and Mathematics - [3Blue1Brown Youtube Channel]

In the episode we discuss,

• A technical breakdown of how data breaches happen
• The concept of threat-hunting and how AI enhances cyber protections
• How companies can stay secure and protect critical entry points
• The most prevalent threats to todays top industries?
• What makes organizations more vulnerable to attacks today, then they've ever been?
• How to leverage AI and protect your company?
• Societal implications of AI technology?
• Ways to get involved in the scientific revolution

In this episode we discuss,

• The state of drug discovery in the US
• Eroom's law and the rising cost of drug research & discovery
• How the scite platform combats the research reproducibility crisis
• The growing call for transparency in healthcare
• The impact machine learning & deep learning has on science
• Conviction in your startup - advice on when to go all in
• An Ai future and what to expect
• Building a startup under various circumstances

In this episode we discuss,

• Data privacy challenges that high growth data startups face
• Whether it pays to prioritize innovation over compliance
• How both startups and enterprises can stay innovative and compliant at the same time
• Tips to speed up what can be a brutal procurement process
• How tech giants like Google are approaching the controversial issue of ethical AI and Ai bias
• Whose responsible for setting rules for Ai ethics, corporations or the government?
• Ways for companies to properly leverage technology like AI, safely and efficiently?

Caroline's Three Crucial Privacy Tips for Companies,

• Incident response plan
• Business continuity plan
• Information security management program

To learn more visit,
Website: https://www.clearops.io/
Linkedin: https://www.linkedin.com/company/clearops-inc
Twitter: https://twitter.com/mcmccaffery

We discuss,

• Breaking into VC
• How the enterprise investment space has transformed due to the rise of AI
• Best practices for enterprise companies to pilot projects with startup companies leveraging deep technologies
• What makes for a good early pilot partner?
• The viability of horizontal companies as they compete against the likes of Google, Amazon, Nvidia, and Microsoft
• How companies can compete with better tooling. We discuss companies & tools like H2O, Data Robot, Data IQ, which are all helping companies build & support models
• Which opportunity areas & industries are still up for grabs
• What startups in the space are taking advantage of better tech (models, protocols, processes, etc), and are creating differentiation in the market

Topics covered include,

• The advancements in Digital Health and it's effects on the Healthcare industry
• How hospitals, universities, and Healthcare providers are implementing AI techniques across their practices and organizations
• How researchers are commercializing their research across universities
• Certain types of AI most commonly used in Digital Health (Image Rec, Machine Learning, Natural Language Processing,etc....)
• The biggest barrier to the technology being implemented
• How technical founders go from technical experts to full-fledge entrepreneurs

Learn more:

• Jake's Linkedin: https://www.linkedin.com/in/jakemendel/
• Jake's Twitter: https://twitter.com/ijakemendel
• Sign up for updates: https://nyc.ai/portfolio/podcast/

Recommended Twitter accounts :

• https://twitter.com/ntdillon
• https://twitter.com/SparksZilla

MBA Program Noted on the Show:

• https://fisher.osu.edu/graduate/wpmba

During my conversation with Justin, I learn how professional modeling and data modeling are not as different as one might think, and I get an inside look into how Justin and the Cherry Pick team think about the future of retail and commerce. The way customers interact and engaged with products is constantly changing and it's important for every brand track the intent behind each brand they create.

Topics touch on are as follows,

• The evolution of the retail beauty industry
• How AI is changing enterprise product strategy
• How social media has changed retail and the way customers interact with brands across platforms
• The similarities between professional modeling and data modeling
• The future of retail marketing in a social first world
• The biggest reason customers & businesses choose to work with early stage companies
• How to navigate the early stages of the startup life cycle

**Learn more: **
Website: Cherrypick.ai
Justin's Twitter: https://twitter.com/jstnstwrt

Stay updated with the show - https://nyc.ai/portfolio/podcast/ - sign up below and we'll keep you updated.