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Kendrick Lamar and Drake: The Rap Battle of the Decade In the world of hip-hop, few rivalries have captured the attention of fans and critics alike as much as the ongoing battle between Kendrick Lamar and Drake. This feud has become the stuff of legend, with both artists dropping diss tracks that are as clever as they are cutting, showcasing their lyrical prowess and deep understanding of the
(kendrick, drake, the, to, is, and, lamar, kendrick lamar)
Best tweets on this topic
drake really sat in the studio for 24 hours just to say "if im a liar... why arent my pants on fire?"
I only want drake to keep replying so I can listen to more kendrick songs
Kendrick and Drake really the Messi and Ronaldo of rap… Kendrick is short and Drake is a rapist
Kids and Their School Life
(kids, to, the, their, is, and, school, in)
Best tweets on this topic
African parents will use Nicolas Jackson as a moral lesson for the reason they keep telling you to barb lowcut. 😂😂
Liam Nissan™
@theliamnissanEven if you found a feral child near the dumpster behind a Dairy Queen and then educated it on absolutely nothing but Dukes of Hazzard reruns and Mountain Dew nutrition facts, that child would still have a better understanding of the U.S. Constitution than Lauren fucking Boebert.
Àbíkẹ́
@gamvchiraiSo Norway banned smartphones in schools and 3 years later, girls’ GPAs are up, their visits to mental health professionals are down 60% and bullying in both boys and girls is down 43-46%. That’s wild
AI Integration and Evolution in Technology and Society The landscape of artificial intelligence (AI) is rapidly evolving, influencing various aspects of technology and daily life. From Apple's potential AI advancements in iPhone and iOS to the challenges with Siri, the journey of AI integration presents a mixed bag of progress and hurdles. The historical CUDA/C++ origins of Deep Learning, highlighted by the ImageNet/AlexNet breakthrough in
(ai, the, to, and, of, for, is, on)
Best tweets on this topic
Marques Brownlee
@MKBHDOn one hand: It seems like it's only a matter of time before Apple starts making major AI-related moves around the iPhone and iOS and buries these AI-in-a-box gadgets extremely quickly On the other hand: Have you used Siri lately?
Andrej Karpathy
@karpathy# CUDA/C++ origins of Deep Learning Fun fact many people might have heard about the ImageNet / AlexNet moment of 2012, and the deep learning revolution it started. https://t.co/2xjLWODMOf What's maybe a bit less known is that the code backing this winning submission to the contest was written from scratch, manually in CUDA/C++ by Alex Krizhevsky. The repo was called cuda-convnet and it was here on Google Code: https://t.co/ch137VSYZ4 I think Google Code was shut down (?), but I found some forks of it on GitHub now, e.g.: https://t.co/zYhzdUxoEN This was among the first high-profile applications of CUDA for Deep Learning, and it is the scale that doing so afforded that allowed this network to get such a strong performance in the ImageNet benchmark. Actually this was a fairly sophisticated multi-GPU application too, and e.g. included model-parallelism, where the two parallel convolution streams were split across two GPUs. You have to also appreciate that at this time in 2012 (~12 years ago), the majority of deep learning was done in Matlab, on CPU, in toy settings, iterating on all kinds of learning algorithms, architectures and optimization ideas. So it was quite novel and unexpected to see Alex, Ilya and Geoff say: forget all the algorithms work, just take a fairly standard ConvNet, make it very big, train it on a big dataset (ImageNet), and just implement the whole thing in CUDA/C++. And it's in this way that deep learning as a field got a big spark. I recall reading through cuda-convnet around that time like... what is this :S Now of course, there were already hints of a shift in direction towards scaling, e.g. Matlab had its initial support for GPUs, and much of the work in Andrew Ng's lab at Stanford around this time (where I rotated as a 1st year PhD student) was moving in the direction of GPUs for deep learning at scale, among a number of parallel efforts. But I just thought it was amusing, while writing all this C/C++ code and CUDA kernels, that it feels a bit like coming back around to that moment, to something that looks a bit like cuda-convnet.
Jim Fan
@DrJimFanWe trained a robot dog to balance and walk on top of a yoga ball purely in simulation, and then transfer zero-shot to the real world. No fine-tuning. Just works. I’m excited to announce DrEureka, an LLM agent that writes code to train robot skills in simulation, and writes more code to bridge the difficult simulation-reality gap. It fully automates the pipeline from new skill learning to real-world deployment. The Yoga ball task is particularly hard because it is not possible to accurately simulate the bouncy ball surface. Yet DrEureka has no trouble searching over a vast space of sim-to-real configurations, and enables the dog to steer the ball on various terrains, even walking sideways! Traditionally, the sim-to-real transfer is achieved by domain randomization, a tedious process that requires expert human roboticists to stare at every parameter and adjust by hand. Frontier LLMs like GPT-4 have tons of built-in physical intuition for friction, damping, stiffness, gravity, etc. We are (mildly) surprised to find that DrEureka can tune these parameters competently and explain its reasoning well. DrEureka builds on our prior work Eureka, the algorithm that teaches a 5-finger robot hand to do pen spinning. It takes one step further on our quest to automate the entire robot learning pipeline by an AI agent system. One model that outputs strings will supervise another model that outputs torque control. We open-source everything! Welcome you all to check out the paper, more videos, and try the codebase today: https://t.co/RwiBT3z78H Code: https://t.co/ERp4Gl0N36
Trading Insights and Wisdom for Aspiring Traders
(trading, you, your, the, and, to, trader, on)
Best tweets on this topic
Tony Trades
@ScarfaceTrades_I made $100k in April trading. You want to know what I did? - I took 1 setup ONLY for 30 days. - I traded the same 1-3 tickers all month. - I took 2 trades on average daily. - I followed my plan for every trade. That’s it. Stop over complicating it, simplicity is key.
Once you finally find your model... Trading will feel like an illegal money printer. You know when to execute, and when to sit back. You know what to look for, and when to look for it. You know how much to risk, and on which accounts. Cheatcode.
Lark Davis
@TheCryptoLarkIf you want to get rich investing, follow this mind-blowingly simple rule: Buy low and sell high. Sounds obvious, yet so many chase highs and ignore the lows. It doesn't get any simpler than this.
How to Gain Followers and Make an Impact on Social Media
(followers, to, the, you, my, in, for, days)
Best tweets on this topic
Alma🌿🍎
@AlmaKRowannope, deleted, not in a mood for drama 😒 Anyway, 500 or 50 000, be the change you want to see in the world You don't need to wait for 100k follows to help smaller accounts, you can do it *now*, with your 150.
impact ≠ going number 1 on spotify impact = touching the lives of millions of fans w their music enough to mobilize them for good causes, cementing their legacy as artists who inspire change in their fans, strenghtening community & solidarity between fans from across the world
Dan Adam
@DanAderm+2347032661011 please everybody tell her to unblock me I wasn't cheating, I was just sleeping 😭💔🤌
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