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Data Science at Home

Francesco Gadaleta
Artificial Intelligence
Machine Learning
Large Language Models
Data Science
Generative AI
Openai
Video Game Development
Neural Networks
Blockchain
Venture Capital
Solar Captains
Kaggle
Robotics
Deep Learning
Vortexnet
Data Privacy
AI Investment Trend
Gamegpt
Blockchain Technology
AGI

Cutting through AI bullsh*t.Come join the discussion on Discord! discord.gg/4UNKGf3

PublishesWeeklyEpisodes325Founded11 years ago
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Latest Episodes

Everyone's quoting Karpathy's "vibe coding" post. Almost no one quotes the part where he says it's for throwaway weekend projects, not production.

Struggling with AI and Software? Here is my new book available for purchase on mythicaltokenmo... more

What do they mean when they say "AI is the new electricity" exactly.

AI is much more than that. It is, in fact, infrastructure and public good.

In this episode I expand on that.

Struggling with AI and Software? Here is my new book available for pu... more

What is the state of AI and videogames? Who is considering it? What are the big fails so far? This and much more is covered in this 1st episode of AI and videogames.

Buy me a coffee ko-fi.com/datascience

Discord Channel: discord.gg/... more

A classifier went from a $200M to a $7.5B valuation in 24 days. We've seen this before: blockchain. Same hype, same irrational money. And no, it's not like the dot-com fiber boom: fiber lasts decades, GPUs go obsolete in a couple of years. Who pays w... more

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Recent Guests

Francesco Gadaleta
Security expert; guest discussing AI-related data security and enterprise tooling
Episode: Productivity is the new data breach (Ep. 301)
Dr. Eliseo Ferrante
Faculty at New York University, Abu Dhabi, and Ville University at Amsterdam
Episode: AGI: The Dream We Should Never Reach (Ep. 296)
Mark Brocato
Head of Engineering at Tonic AI, founder and CEO of Mockaroo
Tonic AI
Episode: When Data Stops Being Code and Starts Being Conversation (Ep. 297)
Matt Lea
Founder of schematical.com and expert in AWS AI implementation
Schematical
Episode: Your AI Strategy is Burning Money: Here's How to Fix It (Ep.295)
Fred Jordan
Co-CEO of FinalSpark, a company focused on developing bioprocessors based on living neurons
FinalSpark
Episode: The Scientists Growing Living Computers in Swiss Labs (Ep. 292)
Sanjoy Chowdhury
Researcher at the University of Maryland College Park
University of Maryland
Episode: When AI Hears Thunder But Misses the Fear (Ep. 291)
Jonas Singer
CEO and founder of Vector Group
Vector Group
Episode: Why VCs Are Funding $100M Remote Control Toys (Ep. 290)
Kenny Vaneetvelde
A seasoned developer and consultant focused on AI.
Episode: AI Agents with Atomic Agents 🚀 with Kenny Vaneetvelde (Ep. 280)
Charles Martin
AI specialist and distinguished engineer in NLP and Search, inventor of WeightWatcher AI
Episode: WeightWatcher: The AI Detective for LLMs (DeepSeek & OpenAI included) (Ep. 278)

Hosts

Francesco Gadaleta
AI and data science professional, founder of Amethix Technologies and author
Frag
AI architect

Reviews

4.3 out of 5 stars from 187 ratings
  • Is there ROI on AI?

    Most tech podcasts assume AI is worth it. Francesco doesn’t. In his conversation with Eliseo Ferrante, they address whether the investment actually makes sense. The discussion is technical, skeptical, and refreshingly honest.

    Apple Podcasts
    5
    WH90069
    United States9 months ago
  • Baseless cynicism

    I was hopeful because I seek out opinions that counter the hype, but all I heard were contrarian takes for the sake of being different.

    Apple Podcasts
    1
    dynobridge
    United States3 years ago
  • Andrea I

    The recent show about databases and their impact on AI felt like unraveling a mystery. I got a full picture of the tech and the challenges in the field. Though not exhaustive, still a very good start. Will explore more!

    Apple Podcasts
    5
    Norincovey
    United States3 years ago
  • TheAlchemist

    In the recent episode, the insights into prompt engineering were akin to unlocking a secret chamber in the world of AI. Mr Francesco seamlessly blended education and discovery, giving listeners a key to understanding the complexity of language models.

    Apple Podcasts
    5
    WilliamEnglis
    United States3 years ago
  • A Knowledge Elevation!

    Finally, a podcast that strikes the perfect balance! Easy not easy. Content always up to date and sexy. thumbs uppp!

    Apple Podcasts
    5
    Harwillcain
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Reviews highlight detailed, technically rich discussions and actionable insight from the host and interview guests.
Listeners often praise clear explanations that make complex AI and data science topics easier to follow.
Some listeners find the material dense, especially when episodes assume substantial technical background.
A minority criticize the skeptical approach as contrarian or question the research and production quality.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#181
Italy/Technology
Apple Podcasts
#46
Poland/Technology
Apple Podcasts
#146
South Korea/Technology
Apple Podcasts
#158
Austria/Technology
Apple Podcasts
#160
Brazil/Technology
Apple Podcasts
#199
Indonesia/Technology

Talking Points

Recent interactions between the hosts and their guests.

AI tips & tricks (Ep. 307)
Q: How do you design effective prompt templates for a domain?
Prompt templates should define a clear role for the assistant, set the tone, specify the context with retrieved documents, enforce constraints (e.g., answer from provided sources), and include explicit instructions to handle uncertainty, enabling domain-specific style and compliance with the organization's standards.
AI tips & tricks (Ep. 307)
Q: When should you use open-source embeddings versus API-based models?
Open-source embeddings are preferred when data residency, full control, and domain-specific fine-tuning are required, especially in regulated environments; API-based models are useful for complex reasoning tasks that require larger parameter counts, though they may increase cost and data exposure risk.
AI tips & tricks (Ep. 307)
Q: What are semantic chunking and fixed-size chunking, and which is better?
Semantic chunking merges semantically similar sentences into larger chunks, reducing redundancy and improving retrieval quality, whereas fixed-size chunking can create many similar chunks that dilute retrieval effectiveness; semantic chunking generally yields better performance.
Your AI Strategy is Burning Money: Here's How to Fix It (Ep.295)
Q: What's your framework for calculating whether an artificial intelligence feature has some kind of positive ROI?
Matt explains it involves looking at both upfront and ongoing investment in terms of engineering hours and infrastructure.
Your AI Strategy is Burning Money: Here's How to Fix It (Ep.295)
Q: How do you help teams figure out if they need AI or traditional methods?
Matt mentions he conducts ROI analysis to determine if tasks can be performed by humans more cost-effectively than developing a custom AI model.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Frequently Asked Questions About Data Science at Home

What is Data Science at Home about and what kind of topics does it cover?

Clear-eyed analysis of artificial intelligence, data science and the technology industry, with particular attention to what works in practice, what the evidence shows and where commercial or policy incentives shape the debate. Episodes often take the form of detailed solo explainers, alongside occasional conversations with industry practitioners and researchers. Recurring host Francesco Gadaleta connects technical subjects such as AI coding tools, retrieval systems and game AI with questions about software quality, economics, regulation and technology's social effects. A second presenter, Frag, joins some discussions. The distinctive approach is skeptical without dismissing the technology: claims are tested against research, implementation ... more

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Which podcasts are similar to Data Science at Home?

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1. Super Data Science: ML & AI Podcast with Jon Krohn
2. DataFramed
3. No Priors: Artificial Intelligence | Technology | Startups
4. Practical AI
5. The a16z Show

How many episodes of Data Science at Home are there?

Data Science at Home launched 11 years ago and published 325 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Data Science at Home?

Recent guests on Data Science at Home include:

1. Francesco Gadaleta
2. Dr. Eliseo Ferrante
3. Mark Brocato
4. Matt Lea
5. Fred Jordan
6. Sanjoy Chowdhury
7. Jonas Singer
8. Kenny Vaneetvelde

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