machine learning

AI and Video Game Development: Navigating the Future Frontier (Ep. 264) [RB]

In this episode we delve into the dynamic realm of game development and the transformative role of artificial intelligence (AI). Join Frag, Jim and Mike as they explore the current landscape of game development processes, from initial creative ideation to the integration of AI-driven solutions. With Mike's expertise as a software executive and avid game developer, we uncover the potential of AI to revolutionize game design, streamline development cycles, and enhance player experiences. Discover insights into AI's applications in asset creation, code assistance, and even gameplay itself, as we discuss real-world implementations and cutting-edge research.
From the innovative GameGPT framework to the challenges of balancing automation with human creativity, this episode offers valuable perspectives and practical advice for developers looking to harness the power of AI in their game projects. Don't miss out on this insightful exploration at the intersection of technology and entertainment!
 
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References
https://mikeyoung44.itch.io/spacefreighter - Itch.io link to play the game
https://discord.gg/yaXgYZ5Ymn - Discord server for the game
https://aimodels.substack.com/ - Mike’s newsletter (links to website too)
 
 

Low-Code Magic: Can It Transform Analytics? (Ep. 260)

Join us as David Marom, Head of Panoply Business, explores the benefits of all-in-one data platforms. Learn how tech stack consolidation boosts efficiency, improves data accuracy, and cuts costs. David shares insights on overcoming common challenges, enhancing data governance, and success stories from organizations thriving with Panoply.
 
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Intrepid AI (https://intrepid.ai) is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months
 
References
Connect and analyze ALL of your data https://panoply.io/
https://blog.panoply.io/raw-data-to-dashboards-in-just-10-steps
https://blog.panoply.io/understanding-etl-extract-transform-and-load-data-to-boost-your-business-intelligence
Blog: The Transformative Power of an All-in-One Data Platform
Whitepaper: Eradicating Platform Inefficiencies

Harnessing AI for Cybersecurity: Expert Tips from QFunction (Ep. 258)

In this episode, we sit down with Ryan Smith, Founder of QFunction LLC, to explore how AI and machine learning are revolutionizing cybersecurity. With over 8 years of experience, including work at NASA's Jet Propulsion Laboratory, Ryan shares insights on the future of threat detection and prevention, the challenges businesses face in maintaining effective cybersecurity, and the ethical considerations of AI implementation. Learn about cost-effective strategies for small businesses, the importance of collaboration in combating cyber threats, and how QFunction tailors its AI solutions to meet diverse industry needs.
 
Sponsors
Arctic Wolf Learn what the new year holds for ransomware as a service, Active Directory, artificial intelligence and more when you download the 2024 Arctic Wolf Labs Predictions Report today at arcticwolf.com/datascience
Intrepid AI (https://intrepid.ai) is an AI assisted all-in-one platform for robotics teams. Build robotics applications in minutes, not months.
QFunction  does cybersecurity differently. By relying on scientific breakthroughs in AI and machine learning, QFunction works within your existing security stack to detect anomalies and threats within your data
 
References
QFunction Blog
Threat Hunting Firewall Logs
Threat Hunting Linux Logs
QFunction GitHub

Debunking AGI Hype and Embracing Reality (Ep. 233)

In this thought-provoking episode, we sit down with the renowned AI expert, Filip Piekniewski, Phd, who fearlessly challenges the prevailing narratives surrounding artificial general intelligence (AGI) and the singularity. With a no-nonsense approach and a deep understanding of the field, Filip dismantles the hype and exposes some of the misconceptions about AI, LLMs and AGI. Join us as we delve into the real-world implications of AI, separating fact from fiction, and gaining a firm grasp on the tangible possibilities of AI advancement. If you're seeking a refreshingly pragmatic perspective on the future of AI, this episode is an absolute must-listen.
 
Filip Piekniewski Bio
Filip Piekniewski is a distinguished computer vision researcher and engineer, specializing in visual object tracking and perception. He approaches machine learning with a pragmatic mindset, recognizing its current limitations. Filip earned his Ph.D. from Warsaw University, where he explored neuroscience and later joined Brain Corporation in San Diego. His extensive study of neuroscience inspired him to develop innovative, bio-inspired machine learning architectures. Filip's unique blend of scientific curiosity and software engineering expertise allows him to quickly prototype and implement new ideas. He is known for his realistic perspective on AI, debunking AGI hype and focusing on tangible advancements.
 
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Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Defense, Robotics and Predictive maintenance.
 
References
https://twitter.com/filippie509
http://blog.piekniewski.info/ (On limits of deep learning and where to go next with AI.)
 
 

Revolutionize Your AI Game: How Running Large Language Models Locally Gives You an Unfair Advantage Over Big Tech Giants (Ep. 226)

This is the first episode about the latest trend in artificial intelligence that's shaking up the industry - running large language models locally on your machine. This new approach allows you to bypass the limitations and constraints of cloud-based models controlled by big tech companies, and take control of your own AI journey.
We'll delve into the benefits of running models locally, such as increased speed, improved privacy and security, and greater customization and flexibility. We'll also discuss the technical requirements and considerations for running these models on your own hardware, and provide practical tips and advice to get you started.
Join us as we uncover the secrets to unleashing the full potential of large language models and taking your AI game to the next level!
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References
https://agi-sphere.com/llama-models/
https://crfm.stanford.edu/2023/03/13/alpaca.html
https://beebom.com/how-run-chatgpt-like-language-model-pc-offline/
https://sharegpt.com/
https://stability.ai/

Deep learning vs tabular models (Ep. 217)

Deep learning methods are not as effective with tabular data. Here is why, and what to do about it.
 
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References
https://paperswithcode.com/methods/category/deep-tabular-learning 
https://m-clark.github.io/posts/2022-04-01-more-dl-for-tabular/
 

Autonomous cars cannot drive. Here is why. (Ep. 210)

If you think that the problem of self-driving cars has been solved, think twice.As a matter of fact, the problem of self-driving cars cannot be solved with the technical solutions that companies are currently considering. Don't get fooled by marketing and PR on social media. Whoever is telling you they solved the problem of driving a vehicle fully autonomously, they are lying.Here is why.
 
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Explore the Complex World of Regulations. Compliance can be overwhelming. Multiple frameworks. Overlapping requirements. Let Arctic Wolf be your guide.Check it out at https://arcticwolf.com/datascience
 
Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Healthcare/RWE, and Predictive maintenance.

Private machine learning done right (Ep. 207)

There are many solutions to private machine learning. I am pretty confident when I say that the one we are speaking in this episode is probably one of the most feasible and reliable.I am with Daniel Huynh, CEO of Mithril Security,  a graduate from Ecole Polytechnique with a specialisation in AI and data science. He worked at Microsoft on Privacy Enhancing Technologies under the office of the CTO of Microsoft France. He has written articles on Homomorphic Encryptions with the CKKS explained series (https://blog.openmined.org/ckks-explained-part-1-simple-encoding-and-decoding/). He is now focusing on Confidential Computing at Mithril Security and has written extensive articles on the topic: https://blog.mithrilsecurity.io/. 
In this show we speak about confidential computing, SGX and private machine learning
 
References
Mithril Security: https://www.mithrilsecurity.io/ 
BindAI GitHub: https://github.com/mithril-security/blindai 
Use cases for BlindAI:Deploy Transformers models with confidentiality: https://blog.mithrilsecurity.io/transformers-with-confidentiality/
Confidential medical image analysis with COVID-Net and BlindAI: https://blog.mithrilsecurity.io/confidential-covidnet-with-blindai/ 
Build a privacy-by-design voice assistant with BlindAI: https://blog.mithrilsecurity.io/privacy-voice-ai-with-blindai/ 
Confidential Computing Explained: https://blog.mithrilsecurity.io/confidential-computing-explained-part-1-introduction/ 
Confidential Computing Consortium: https://confidentialcomputing.io/ 
Confidential Computing White Papers: https://confidentialcomputing.io/white-papers-reports/ 
List of Intel processors with Intel SGX:https://www.intel.com/content/www/us/en/support/articles/000028173/processors.html 
https://github.com/ayeks/SGX-hardware 
Azure Confidential Computing VMs with SGX:Azure Docs: https://docs.microsoft.com/en-us/azure/confidential-computing/confidential-computing-enclaves 
How to deploy BlindAI on Azure: https://docs.mithrilsecurity.io/getting-started/cloud-deployment/azure-dcsv3 
Confidential Computing 101: https://www.youtube.com/watch?v=77U12Ss38Zc 
Rust: https://www.rust-lang.org/ 
ONNX: https://github.com/onnx/onnx
Tract, a Rust inference engine for ONNX models: https://github.com/sonos/tract
 

Is studying AI in academia a waste of time? (Ep. 202)

Companies and other business entities are actively involved in defining data products and applied research every year. Academia has always played a role in creating new methods and solutions/algorithms in the fields of machine learning and artificial intelligence.However, there is doubt about how powerful and effective such research efforts are.Is studying AI in academia a waste of time?
 
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Explore the Complex World of Regulations. Compliance can be overwhelming. Multiple frameworks. Overlapping requirements. Let Arctic Wolf be your guide.Check it out at https://arcticwolf.com/datascience
 
Amethix works to create and maximize the impact of the world’s leading corporations and startups, so they can create a better future for everyone they serve. We provide solutions in AI/ML, Fintech, Healthcare/RWE, and Predictive maintenance.
 

Online learning is better than batch, right? Wrong! (Ep. 200)

In this episode I speak about online learning systems and why blindly choosing such a paradigm can lead to very unpredictable and expensive outcomes.Also in this episode, I have to deal with an intruder :)
 
 
Links
Birman, K.; Joseph, T. (1987). "Exploiting virtual synchrony in distributed systems". Proceedings of the Eleventh ACM Symposium on Operating Systems Principles - SOSP '87. pp. 123–138. doi:10.1145/41457.37515. ISBN 089791242X. S2CID 7739589.