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AI Papers Podcast Daily
United States
Приєднався 24 жов 2024
Welcome to AI Daily Podcast, your go-to source for daily insights into the cutting-edge world of artificial intelligence! Join hosts Alice Mallory and Bob Trent as they explore the latest AI research papers. Every episode breaks down complex concepts and discoveries, making them accessible for AI enthusiasts, researchers, and curious minds alike. Whether you're looking to stay updated on the newest breakthroughs or deepen your understanding of AI, AI Daily Podcast is the perfect companion for your daily knowledge fix. Subscribe for fresh episodes every day!
DeepSeek-V3: A 671B Parameter Mixture-of-Experts Language Model
This technical report describes DeepSeek-V3, a large language model with 671 billion parameters (think of them as tiny knobs controlling the model's behavior). DeepSeek-V3 uses a clever "Mixture-of-Experts" (MoE) approach, where only 37 billion parameters are active for processing each word, making it efficient and affordable to train. It's like having a team of experts where only the most relevant ones chime in for each task! DeepSeek-V3 excels in understanding and responding to instructions, performing well in tests like MMLU and DROP. It also shows remarkable abilities in math and coding challenges, beating other open-source models and sometimes even matching top closed-source models like GPT-4. The report explains the model's unique design and training process, highlighting its ability to handle long chunks of text (up to 128,000 words!) and its innovative use of low-precision calculations to save resources.
github.com/deepseek-ai/DeepSeek-V3/blob/main/DeepSeek_V3.pdf
github.com/deepseek-ai/DeepSeek-V3/blob/main/DeepSeek_V3.pdf
Переглядів: 19
Відео
The Secret Sauce of AI: Uncovering the Provenance of Multimodal Data
Переглядів 27 годин тому
This paper looks at the huge amount of data that is used to train AI models. The researchers investigated a large number of datasets, which are like giant collections of information, that are used to teach AI how to understand text, speech, and video. They found that a lot of this data comes from websites like UA-cam and books, which can sometimes have problems with copyright and permissions, m...
Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
Переглядів 442 години тому
This research paper explores how to protect private information in AI systems, especially those that use Retrieval-Augmented Generation (RAG). RAG systems help large language models (LLMs) access and use external knowledge bases to provide better answers. However, hackers can trick these systems into revealing private information from these knowledge bases. The authors developed an automated at...
OpenAI Deliberative Alignment: Reasoning Enables Safer Language Models
Переглядів 449 годин тому
Researchers created a new way to train large language models (LLMs) to be safer, called Deliberative Alignment. This method teaches the models safety rules directly and trains them to think about these rules before answering a question. This helps prevent the models from giving harmful answers or refusing to answer harmless questions. They tested this method on OpenAI's o-series models and foun...
Forest-of-Thought: Scaling Test-Time Compute for Enhanced LLM Reasoning
Переглядів 269 годин тому
This research paper describes a new method called Forest-of-Thought (FoT) designed to help large language models (LLMs) solve problems better. LLMs, like the ones that power chatbots, are good at language tasks but struggle with complex reasoning. FoT works by using multiple “thinking trees” to explore different ways to solve a problem. Imagine each tree representing a different approach to fin...
Parallelized Autoregressive Visual Generation
Переглядів 209 годин тому
This research paper describes a new method called PAR, or Parallelized Autoregressive Visual Generation, to create images and videos faster using computer models. Typically, these models create images one piece at a time, which can be slow. PAR speeds up the process by figuring out which pieces of the image are not strongly connected to each other and creating those pieces at the same time. Ima...
LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
Переглядів 1512 годин тому
LongBench v2 is a new test to see how well AI can understand and answer questions about really long texts, like books, articles, and code. The test has over 500 questions, and even experts have trouble answering them quickly. The test covers lots of different types of questions, like figuring out who did a crime in a story, translating a new language, and understanding how a computer program wo...
SWE-Bench: Evaluating Language Models on Real-World GitHub Issues
Переглядів 6312 годин тому
This research paper introduces SWE-Bench, a new way to test how good large language models are at solving real problems with computer code. It uses real problems and code from GitHub, a website where programmers share and work on code together. These problems are more complex than what language models are usually tested on, requiring them to understand lots of code and make changes across multi...
FrontierMath: A Benchmark for Advanced Mathematical Reasoning in AI
Переглядів 5612 годин тому
This research paper introduces FrontierMath, a collection of very hard math problems designed to test how well AI can solve advanced math. The problems in FrontierMath are brand-new and cover many different areas of math, like algebra and calculus. The researchers found that even the smartest AI today can only solve a tiny fraction (less than 2%) of these problems. To make sure the problems wer...
GPQA: A Graduate-Level Google-Proof Q&A Benchmark
Переглядів 1412 годин тому
This research paper describes the creation and analysis of GPQA, a new set of multiple-choice questions designed to be very hard to answer, even with the help of Google. The questions cover advanced topics in biology, physics, and chemistry, and were written and checked for accuracy by experts with PhDs in those fields. The researchers made sure the questions were extra tough by having other ex...
Monte Carlo Inference for Semiparametric Bayesian Regression
Переглядів 4114 годин тому
This excerpt from the Journal of the American Statistical Association talks about a new way to do Bayesian regression, a type of statistical analysis used to figure out the relationship between different things. Regular Bayesian regression can be tricky when the data doesn't fit certain patterns. To make it easier to work with different types of data, this paper suggests using something called ...
OpenAI o3 Breakthrough High Score on ARC-AGI Competition: Has AGI Been Achieved?
Переглядів 8414 годин тому
OpenAI has created a new AI model, called o3, that is much better at solving problems it has never seen before compared to older AI systems like GPT-3 and GPT-4. This is a big deal because for many years, AI researchers have been trying to create AI that can learn new things quickly, just like humans. o3 was tested on a special set of problems called ARC-AGI which are designed to be very hard f...
SciAgents: Automating Scientific Discovery
Переглядів 1616 годин тому
This research paper talks about a new computer program called SciAgents that can help scientists discover new things, especially about materials inspired by nature. SciAgents uses a special database called a knowledge graph that contains lots of scientific information about different materials and how they work. The program also uses large language models (LLMs) like ChatGPT, which are really g...
Qwen2.5 Technical Report
Переглядів 2416 годин тому
This report describes Qwen2.5, a group of large language models (LLMs) designed for a wide range of uses. Qwen2.5 has been significantly improved from earlier versions, using a massive dataset of 18 trillion words and phrases for training. This extensive training gives Qwen2.5 a strong understanding of general knowledge, specialized expertise, and reasoning abilities. It also excels in followin...
Enhancing LLM Reasoning with Argumentative Querying
Переглядів 1916 годин тому
This research paper introduces a new technique called Critical-Questions-of-Thought (CQoT) to help Large Language Models (LLMs), which are like super-smart computer programs, get better at solving logic and math problems. The idea is that by asking the LLM a series of "critical questions" based on how humans argue and reason, the LLM can double-check its work and avoid making mistakes. This is ...
ModernBERT: A Highly Efficient Encoder-Only Transformer Model
Переглядів 17216 годин тому
ModernBERT: A Highly Efficient Encoder-Only Transformer Model
Alignment Faking in Large Language Models
Переглядів 6719 годин тому
Alignment Faking in Large Language Models
Contextualized Recommendations Through Personalized Narratives using LLMs
Переглядів 1319 годин тому
Contextualized Recommendations Through Personalized Narratives using LLMs
Benchmarking Large Language Model Agents on Real-World Tasks
Переглядів 1319 годин тому
Benchmarking Large Language Model Agents on Real-World Tasks
Bipartisan Artificial Intelligence Task Force Report on Artificial Intelligence - December 2024
Переглядів 321 годину тому
Bipartisan Artificial Intelligence Task Force Report on Artificial Intelligence - December 2024
FACTS Grounding Leaderboard: Benchmarking LLMs' Factuality
Переглядів 1621 годину тому
FACTS Grounding Leaderboard: Benchmarking LLMs' Factuality
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Переглядів 2721 годину тому
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Relational Neurosymbolic Markov Models
Переглядів 1021 годину тому
Relational Neurosymbolic Markov Models
Stable Reasoning in LLMs: A Novel Evaluation Metric and Benchmark
Переглядів 1021 годину тому
Stable Reasoning in LLMs: A Novel Evaluation Metric and Benchmark
KPMG 20th annual Global Semiconductor Outlook
Переглядів 17День тому
KPMG 20th annual Global Semiconductor Outlook
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Переглядів 26День тому
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Byte Latent Transformer: Patches Scale Better Than Tokens
Переглядів 256День тому
Byte Latent Transformer: Patches Scale Better Than Tokens
Guide to Essential Competencies for AI
Переглядів 5814 днів тому
Guide to Essential Competencies for AI
Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning...
Переглядів 3714 днів тому
Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning...
:D
Thanks!
This is fake AI-generated audio, made by the Google tool that can take a topic and create a 2-person discussion about it. This is not real people.
I watched your AI-generated podcast video on UA-cam about the research paper. Could you share how you created it, including the tools and techniques used? Thanks!
Awesome pod! I love how they always make complex topics easy to understand and it doesn't feel robotic at all. I've found you can also customize the introduction by customizing the podcast generation. Rather that "Welcome to the deep dive" you can ask it to start with "Welcome to the AI Papers podcast"
This did not age well... o3 has hit 25%!!
o1 had the frontiermath in its training data. So o3 got a peek into it already and the performance has been gamed to meet the benchmark via memorization not reasoning. I have played enough with o3 pre-release version. You will know it naturally when it doesn't get better as you expect it to be from o1
A nice use of notebook lm maybe you should provide credit
oh it is notebookLM! cool.
are these based on notebookLM?
Great analysis, thank you! Could you help me with something unrelated: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How can I transfer them to Binance?
Thanks for this. o1 systems report is pretty intense too.. you should talk about it.
It’s ironic that the podcast “speakers” are AI LOL
this is so uncanny valley 😬 but yeah, you should make it 100% clear that the podcast is generated using AI
this is quite a good way to absorb a scientific paper. But you should be clear that the podcast itself is AI generated
This is genuinely Amazing. Keep going!!!!
Wow the guest thanked the host for joining as an expert! AI vs AI
Thanks for the upload, however to anyone who is interested in the subject I would highly recommend to have a quick glimpse at the actual paper. Especially Abstract, Conclusion and Results are written in quite easy language and are just sooo much more focused than this AI podcast.
Great content, as always! I need some advice: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How should I go about transferring them to Binance?
🤖
Feedback loop. We either make an AI that aligns with our views and the planet moves on without us or we learn to trust infinite diversity in infinite combinations and accept the differences that AI brings, whether it kills us or not.
First!... Only?... Maybe.
Finally, ai generated podcast
interesting paper and podcast. But it is confusing to listen to because you switch roles so many times. If the same person is explaining then asking questions like he doesn't know what is going on, it makes it seem unauthentic and more importantly confusing. Also you don't need to say something (or make a sound) after every single sentence the other person says. Thanks for the effort
Alice and Bob, eh? You thought AI interested people wouldn’t know NotebookLM when they heard it? Just be upfront about it.
Considering the topic, it is kinda funny, though.
Amazing! Could you share the original source or sources from which the podcast was built on?
Good papar. Good video.
Jesus, can you be MORE annoying with these two voices?! Blocking your whole channel.
is this produced by NotebookLM?
sounds like it is
Surprised no one commented. Great podcast