16:13
The impact of DeepMind's Research on Machine Learning for Quantum Error Correction
00:42
Trying to model Quantum Bits
05:45
New York Times "AI OutPerforms Doctors" is Clickbait Garbage
10:32
Understanding the different kinds of Data Leakage in Machine Learning
00:13
Putting an LLM in the Wild
07:46
Understanding one of Machine Learning's biggest cliche's- why Good Data Matters
13:13
OpenAI's claims about o1's Medical Diagnosis are dangerous
07:09
Why Meta Open Sourced their best LLM but Google didn't
03:41
Why Mean Squared Error Hates Outliers (Machine Learning Basics).
18:19
Why Retrieval Augmented Generation is such a big deal in AI
00:13
Growing of 2D patterns and damage recovery (Mordvintsev et al., 2020).
11:28
How SWE Bench solves Complex Software Problems with Agents Computer Interfaces and LLMs
00:09
Software Engineers waiting for their code to finish building
02:53
One simple tweak will skyrocket your deep learning embeddings
04:38
How the Death of Job Security leads a loss of innovation
10:29
Why "AI for non-technical professionals" courses are a waste of time
18:51
MatMul-Free LLMs will change everything
29:03
Understanding Kolmogorov–Arnold Networks: Possible Successors to MLPs?
07:15
How the loss of Job security increases wealth inequality and drops social mobility
19:51
How you can improve Deep Learning with Domain Adversarial Neural Networks
06:16
Why large batch sizes lead to worse generalization in Deep Learning
19:29
How to build Large AI Models like ChatGPT efficiently
19:55
How Diffusion Models are Improving AI
03:58
Super Important Announcement- Plans for the YouTube channel going Forward
00:10
AlphaFold 3 improving enzyme predictions
02:25
Why you should consider using Mixture Models in Machine Learning
20:11
Why Meta released Llama 3 Open Source and MS is fighting against OS Foundation Models.
06:07
How Influencers, Businesses, and Politicians manipulate you online part 1: Availability Bias.
01:52
A reel about Google's Pathways Architecture for training LLMs
19:40
Devin AI's demos are lying. Tactics used to generate hype (
05:39
Why LSTMs are good for weather forecasting.
20:36
How Amazon AI reaches completion faster with FINGER.
12:43
Google's Revolutionary LLM Training Architecture: Understanding Pathways
06:37
How do Neural Networks Converge in an infinite search space
04:12
Tree Based Models are Better than Neural Networks on Jagged Decision Boundaries
06:03
Why you should care about UFC's 334 Million Dollar Settlement with Fighters
05:33
Why I Write/Make Videos
20:04
How Amazon makes Machine Learning for Alexa AI Trustworthy
06:27
The Macroeconomics Principle that helps us understand why all systems eventually fail: Goodharts Law
05:34
Investing will NOT make you rich
16:30
Why Hallucinations are inevitable in Large Language Models. Machine Leaning Made Simple
03:01
A reel about Natural Gradients and why and how they might replace SGD
19:15
Understanding Natural Gradient Descent. Why SGD is not good for Multi-Task learning and AGI.
21:31
How Google solved Geometry with AI and LLMs: a deeper look into AlphaGeometry. ML Techniques
03:06
AlphaGeometry- How Google taught AI to solve Geometric Proofs [Reels]
32:06
The Rise of AI as Magic and Why It's Hurting You
07:22
Why Tesla Shareholders are suing Elon Musk
19:19
Why and How is Neural Architecture Search biased
07:54
Why Mass Layoffs Happen Part 2- R&D as a Commodity
12:26
Coshnets: Improving Convolutional Neural Networks with Complex Numbers. ML techniques
07:55
Why Mass Layoffs Happen Part 1- CEOs profit from conducting mass layoffs.
04:31
Why we can embed data from multiple modalities into the same vector space
01:44
SPACs- one of the hottest scams on Wall Street
09:43
What is Population Based Meta Learning- The Future of AGI/Foundation Models
09:36
Create Better Foundation Models with Meta Learning
01:23
Big Tech Companies exploit child labor in AI and Electronics
12:49
Reacting to OpenAI Dev Day Announcements- Are the new GPT updates that good?
12:19
Build your own Anti-Signal Jamming tools with AI. AI in Censorship Ep 2
11:24
How to break automated government censors with evolutionary algorithms. AI in Censorship Ep 1
03:03
What is federated learning and why do companies like Amazon love it?
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About
Computer Science and Computational Math Double Major at Rochester Institute of Technology. Established track record of combining software engineering, mathematical/statistical data analysis, and machine learning. I write high-performing code and scripts for organizations to help them generate more revenue, identify areas of investment, isolate redundancies, and automate processes. Involved in Machine Learning research. Looking to work in Machine Learning, Software Development, Artificial Intelligence, and Research into AI Safety
Years of Machine Learning Experience, Software Development, and Android Development working on a diverse set of Problems at various institutions. Content Creator focusing on Machine Learning, Computer Science, and Math Related content. Content used by people worldwide.
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