AI Daily
Daily insights on the latest news, innovations, and tools in the world of AI.
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Top 10 AI Daily Episodes
Goodpods has curated a list of the 10 best AI Daily episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to AI Daily for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite AI Daily episode by adding your comments to the episode page.
06/16/23 • 18 min
Welcome to AI Daily, your go-to podcast for the latest updates in the world of artificial intelligence! In today's episode, we have some banger stories lined up for you. Join us as we dive into the exciting advancements in the realm of Mechanical Turk, the impact of AI in the EU Parliament, and a cutting-edge multimodal technology called Video LLaMA.
Key Points:
Video LLaMA
A new paper called Video LLaMA, which focuses on turning video and audio into text and understanding them better.
The paper addresses two main challenges: capturing temporal changes in video scenes and integrating audio and visual signals.
The model showcased in the paper demonstrates accurate predictions and understanding of videos, including analyzing images, audio, facial expressions, and speech.
The availability of the model for public use is uncertain as it is currently a research paper, but it highlights the potential of leveraging AI tools like Image Binds and audio transformers to enhance video understanding.
Mechanical Turk
A study reveals that a significant portion (around 36-44%) of text summarization tasks on Mechanical Turk are being done by AI models like ChatGPT instead of humans.
The displacement of human workers by synthetic models raises concerns about the availability and quality of real data for training larger language models like GPT-4 and GPT-5.
Detecting synthetic data generated by language models is challenging, and specialized classifiers may be required to distinguish between human-generated and AI-generated text.
The increasing reliance on AI models for tasks like text summarization may lead to the introduction of stricter verification measures, such as keystroke tracking or biometric testing, to ensure authenticity in online assessments and proctoring.
EU Parliament & AI
The EU Parliament is taking steps towards AI regulation, although the specifics and implications are unclear.
There are concerns about redundancy in creating separate AI-specific regulations when existing laws could cover related aspects such as data privacy.
The potential impact of AI regulation on startups and small players is uncertain, as compliance requirements and limitations on training AI models could arise.
The regulation aims to address issues like transparency, disclosure of AI-generated content, and prohibitions on certain applications like social scoring and real-time facial recognition. However, some argue that these issues can be legislated without directly tying them to AI.
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08/03/23 • 11 min
Welcome to AI Daily! Join hosts Farb, Ethan, and Conner as they explore three groundbreaking AI stories First up, HierVST Voice Cloning - Experience zero-shot voice cloning with impressive accuracy using just one audio clip. Next, NVIDIA Perfusion - a small, powerful personalization model for text images, using key locking to maintain consistency. Lastly, Meta's AudioCraft - the fusion of music generation, audio generation, and codecs into one open-source code base, creating high-fidelity outputs.
Quick Points
1️⃣ HierVST Voice Cloning
Zero-shot voice cloning system achieves accurate outputs with just one audio clip.
Uses hierarchical models for long and short-term generation understanding.
Potential challenges in handling longer clips and need for further fine-tuning.
2️⃣ NVIDIA Perfusion
Personalization model for text images with key locking for subject consistency.
Only 100 kilobytes, trains in four minutes, and outperforms other models.
Open-source codebase, but may need improvements for human subjects.
3️⃣ Meta’s AudioCraft
Audio generation, music gen, and codecs combined into an open-source codebase.
High-fidelity outputs, 30 seconds of sounds, compressing audio files efficiently.
Meta making strides in audio AI, impressively opens research use for community.
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08/16/23 • 11 min
Welcome back to AI Daily. In this episode, hosts Conner, Ethan, and Farb delve into three fascinating stories. First, Microsoft introduces an enterprise-specific ChatGPT version, self-hosted on Azure's private cloud. Next up, Global competition intensifies as countries race to bolster semiconductor production. Germany secures an $11 billion TSMC chip plant, while Texas welcomes a $1.4 billion semiconductor facility. Finally, Nvidia and HuggingFace join forces to enhance cloud offerings. Nvidia aims to expand its cloud services and connect directly with developers, positioning itself as more than a chip manufacturer.
Quick Points
1️⃣ Microsoft Azure ChatGPT
Microsoft unveils Azure ChatGPT for enterprises, self-hosted on Azure's private cloud.
Repository briefly removed amid potential conflicts, highlighting unique deployment benefits.
Tailored for businesses, offering data control and secure sandbox for AI-powered interactions.
2️⃣ SemiConductor Manufacturing
Global competition heats up as countries vie for semiconductor manufacturing dominance.
Germany secures $11 billion TSMC chip plant, bolstering European presence.
Texas welcomes $1.4 billion semiconductor facility, reflecting chips' pivotal role in technology evolution.
3️⃣ NVIDIA-HuggingFace Partnership
Nvidia teams up with Hugging Face, aiming to strengthen cloud services presence.
Nvidia's expansion into direct cloud hosting aims to compete with established players.
The collaboration enhances accessibility to GPUs, potentially reshaping Nvidia's cloud industry involvement.
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06/07/23 • 17 min
Don't miss this special edition of AI Daily, where we dive into the exciting announcements from yesterday's WWDC event. Join us as we explore all things AI related and discuss the groundbreaking features that were unveiled. We'll cover everything from transformers to neural networks, bringing you the latest insights into the world of AI.
Key Points:
Apple did not mention AI during the WWDC event, but they referenced technologies like transformers and neural networks.
Transformers have been implemented to improve autocorrect, keyboard experience, and dictation on iPhones.
Apple's new M2 Ultra GPU is useful for training transformer models.
Apple introduced the Curated Suggestions API for creating multimedia journals on Apple devices.
The Curated Suggestions API uses on-device neural networks for privacy.
Live voicemail transcribes voicemails in real-time on the device and allows users to answer calls midway.
Siri now supports back-to-back commands and utilizes audio transformer models.
FaceTime reactions allow users to separate subjects from photos and create stickers.
ML or AI is used to differentiate subjects from the background in photos and FaceTime videos.
Apple's AirPods and AirPlay have adaptive audio features that adjust volume and transparency based on user interactions, possibly using audio transformer models.
Apple's Vision Pro includes digital avatars that reconstruct a user's face based on scans and movements, but chin detection technology is still in development.
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Transformer Auto Correct & Dictation
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05/17/23 • 13 min
Join us on this episode of AI Daily as we discuss three exciting news stories. First, we delve into Sam Altman's testimony in front of Congress, where he discusses the future of AI regulation and its impact on the economy. Then, we explore Quora's Poe API, a groundbreaking web browser for LLMs that allows developers to bring their own language models to the platform. Finally, we cover Apple's latest accessibility announcements, including live speech and personal voice advancements. Tune in to gain insights and discover the intriguing developments in the world of AI.
Main Take-Aways:
Sam Altman's testimony:
Sam Altman testified in front of the Senate Judiciary subcommittee on Privacy, Technology, and the Law about AI regulation.
He emphasized the importance of AI safety and the future of the economy with AI.
Altman's approach of being open and accessible to lawmakers was praised.
Senators expressed surprise that technology was actively seeking regulation.
The hearing focused on past mistakes in technology, such as social media, and the need for good regulation.
Quora Poe API:
Quora introduced the Poe API, positioning itself as a web browser for language models (LLMs).
Poe aims to allow developers to integrate any type of LLM, including custom models, into their applications.
The API offers features like language chaining, monetization, and human feedback for reinforcement learning from humans.
It provides a one-click replica for easy API usage and built-in integrations with LLM frameworks.
The focus is on enabling developers to bring full LLM experiences to users, not just plugins.
Apple's latest accessibility announcements:
Apple announced advanced speech accessibility features, including live speech and personal voice.
The focus is on making AI technologies accessible and beneficial for people with disabilities.
Users can train their voices on their devices, creating custom voice models for communication.
The Magnifier app allows users to point at objects and have the labels or buttons read aloud.
These accessibility features leverage Apple's on-device machine learning capabilities and are expected to roll out later in the year, likely with the next OS release.
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Transcript:
Conner: Good morning. Good morning. Welcome to another episode of AI Daily. We got three pretty great stories for you guys today, starting with first we have Sam Altman's testimony. Uh, this morning in front of Congress, the Senate Judiciary subcommittee on Privacy technology and the law interviewed him this morning, uh, parking a lot about AI regulation.
He was joined by a professor at from NYU. And also by, uh, Christina Montgomery, IBM's Chief Privacy and Trust Officer and the Senate, and Sam Altman and the other representatives were all extremely concerned about the future of AI safety, the future of the economy with ai. Farb, Any
Farb: thoughts? Uh, you know, I think Sam has been giving a masterclass in how to do this stuff correctly.
The bottom line is people want to know who the leaders are that are building and controlling these massively powered technologies, ma, massively powered technologies. Obviously the politicians want to know who these people are. The politicians want to be understood by their constituents as caring about these things, taking the steps to get these leaders in front of them to speak.
And Sam is. You know, getting ahead of the story just about every time and a, a real blueprint for other tech leaders. And clearly he's watched folks in the past, other big tech leaders from big companie...
05/12/23 • 12 min
Join us on AI Daily as we dive into the latest breakthroughs in the world of AI! In today's episode, we discuss a game-changing update in token limits with Anthropic Claude 100K Context. We also explore the fascinating advancement of StabilityAI’s Animation SDK and its implications for creatives and filmmakers. And finally, we cover Meta AI's exciting advertising innovations, revolutionizing generative AI in the ad space! Tune in now for all the AI news you need to stay ahead!
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Nivi’s Twitter (Tweet on Naval & Cluade+)
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05/31/23 • 13 min
Welcome to another exciting episode of AI Daily! In today's edition, we have three captivating news stories lined up for you. First up, we have the remarkable achievement of NVIDIA, as they join the exclusive club of trillion-dollar companies like Amazon, Microsoft, and Apple. Next, we explore an intriguing project called Voyager. This innovative approach to training AI models in Minecraft using the GP4 framework has revolutionized the process. Our final story showcases Google's project SoundStorm, which introduces efficient parallel audio generation. This development allows for the rapid creation of audio by leveraging parallel processing. Join us for this episode of AI Daily as we dive deep into these captivating news stories and uncover the incredible potential they hold for the future.
Key Take-Aways:
NVIDIA Becomes $1T Company:
NVIDIA breaks trillion-dollar market cap, joining Amazon, Microsoft, and potentially Apple in an exclusive club.
NVIDIA's market leadership and monopoly status in the chip industry are clear, with their critical role in the AI ecosystem and impressive demos.
The future of microprocessors is promising, with potential for multiple trillion-dollar companies in the industry.
AMD poses competition in the enterprise market, but NVIDIA's focus on AI and scaling quickly may solidify their position. Other players may emerge in the next few years, including Apple, Google, Microsoft, and Meta, with their own in-house chips. The onshoring of chips in America may also contribute to the rise of upstart companies.
Voyager
Voyager is a project in Minecraft where a GP4 model is trained by iterating on its own code base of skills, saving them in its memory for future use.
The use of LLMs and self-correcting error loops in Voyager resulted in faster progress in Minecraft compared to traditional reinforcement learning techniques.
The training and improvement of models like Voyager can be recursive, either internally with LLMs training LLMs or externally using pipelines and frameworks to continually enhance performance.
The approach taken in Voyager has potential applications in real-world robotics, where robots can learn and improve their skills by iterating on their own internal code. This recursive model has significant implications for accelerating AI development.
SoundStorm
Google's project SoundStorm focuses on efficient parallel audio generation, allowing the generation of a significant amount of audio in a short time.
The model shows promise in terms of speed and quality, with the ability to generate 30 seconds of audio in just half a second.
Currently, the project is not publicly available, but Google is showcasing its AI projects, and it is expected that it will be accessible in the future.
The improved speed in audio generation opens up new possibilities for real-time applications, such as generating audio for NPCs in AI games.
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StyleAvatar3D, Gorilla, & GILL
AI Daily
06/01/23 • 15 min
In today's episode, we have three exciting stories to share with you. First up is GILL, a groundbreaking method that infuses image recognition capabilities into language models. With GILL, you can now send images to chatbots and receive responses in the form of edited images or detailed explanations. It offers a unique approach to understand and respond to images without the need for extensive multimodal training. Next, we have StyleAvatar3D, a remarkable advancement in 3D avatar generation. This technology allows for high-fidelity and consistent 3D avatars with various poses and styles. Unlike previous methods, StyleAvatar3D maps out the three-dimensional space to create a more realistic and immersive experience. This development opens up new possibilities in gaming and social applications. Lastly, we explore Gorilla, the API app store for language models. Gorilla connects LLMs with thousands of APIs, offering users a vast selection of tools to complete tasks. What sets Gorilla apart is its ability to eliminate hallucinations and provide accurate and reliable API suggestions. With 1,640 APIs available, this model proves to be a powerful and valuable resource. The AI revolution continues, and these stories demonstrate the incredible progress being made in the field.
Key Take-Aways:
GILL:
Gil is a method that infuses image encoder and decoder into Ella lambs, enabling them to recognize, understand, and respond to images.
Gil offers a unique approach by injecting image embeddings into LLMs, allowing for various use cases such as image editing, image explanations, and image injection into conversations.
The integration of an encoder in Gil enables both image generation and image retrieval, expanding its capabilities beyond traditional multimodal models.
Gil's open-source code sets it apart from Meta's multimodal work, offering accessibility and potential real-world applications in image-based communication.
StyleAvatar3D:
StyleAvatar3D introduces image text diffusion for high-fidelity 3D avatar generation, allowing for a wide range of avatars with different poses and styles in a complete 3D space.
The significance of the 3D aspect lies in the visual accuracy and consistency that is challenging to achieve with traditional stable diffusion methods. StyleAvatar3D offers both the generation of 3D images and the ability to maintain consistency in attributes and appearance.
Unlike previous avatar generators that relied on stitching together 2D images, StyleAvatar3D maps out the three-dimensional space, providing a more consistent and immersive experience for games and social platforms.
The introduction of true 3D assets has marked a significant leap forward, enabling the creation of realistic and dynamic visuals in game development and other applications.
Gorilla:
Gorilla is an API app store for LLMs that connects the LLM world with the vast world of APIs, offering thousands of APIs for completing user tasks.
One of Gorilla's key achievements is addressing hallucinations that exist in models like GPT-4, providing accurate API recommendations instead of generating random information.
The Gorilla model is entirely open source, with the training still in progress. However, the inferencing, dataset, and evaluations are openly available. It boasts a wide range of 1,640 APIs that can be called, demonstrating its capabilities against built-in spotlights like Apple's and showcasing superior performance.
Fine-tuning the model on APIs proves to be more effective than prompting, reducing hallucinations and improving accuracy. The architecture's ability to quickly update APIs within the model allows for faster contributions and continuous improvement without the need for complete retraining.
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AI Breakthroughs: New LIMA Model, CoDi Multimodal Generation, Mind-to-Video, & ChatGPT App Reviews.
AI Daily
05/23/23 • 11 min
In this episode, we delve into three exciting news stories. First up, we explore the remarkable LIMA model, a 65 billion parameter model that performs almost as well as GPT4 and even outperforms Bard and Da Vinci! Find out how Meta's innovative approach is revolutionizing the open source AI realm. Next, we unravel the fascinating CoDi model, which utilizes compositional diffusion for generating multimodal outputs. Learn how this powerful model can transform text and audio inputs into stunning videos. Lastly, we uncover the mind-boggling Mind-to-Video technology that reconstructs videos based on brain activity. Join us as we discuss the possibilities and implications of mapping the human mind. We also discuss hilarious ChatGPT App reviews, which you won’t want to miss!
Main Take-Aways:
LIMA Model
The Lima model is a large 65 billion parameter LLaMa model that was fine-tuned on a thousand carefully curated responses.
It performed almost as well as GPT4 and even better than models like Bard and Da Vinci.
Meta has released the Lima model as an open source model, showcasing their commitment to staying up-to-date in the AI field.
Lima's approach differs from other models by using supervised examples instead of human feedback, resulting in impressive responses.
This development is significant because it brings another open source model closer to competing with the massive models trained by OpenAI, providing an alternative approach to alignment.
CoDi
CoDi is a model that specializes in any-to-any generation using compositional diffusion.
Unlike other models that primarily process text, CoDi is designed for multimodal tasks, allowing users to input combinations of text, audio, and video to generate corresponding outputs.
CoDi can generate videos based on text and audio inputs or produce new text outputs based on two different text inputs.
Understanding context is crucial for CoDi, as it needs to comprehend the relationships between different modalities to provide accurate and comprehensive results.
CoDi appears to be an open-source model, potentially an enhanced version of Meta's previously released ImageBART, although a direct comparison has not been made yet. The code for CoDi is likely available for use.
Mind-to-Video:
The team has developed a mind-meets-video model that reconstructs videos based on brain activity captured through fMRIs.
The training process involves pairing fMRI data with corresponding videos, allowing the model to learn the relationship between brain signals and video content.
The model aims to capture what a person is remembering or perceiving by analyzing their brain activity and finding similar videos from the training set.
Although it is not yet capable of mind reading, the model provides insights into how the brain processes and represents visual information.
The team's previous work focused on mind-to-image generation, and this mind-to-video model represents an impressive advancement, achieving a 45% increase in accuracy compared to previous methods.
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06/09/23 • 14 min
Welcome to an exciting episode of AI Daily, where we discuss three captivating stories: Bard updates, ARTIC3D research paper, and DeepMind's Alpha Dev discovery. We delve into the remarkable advancements in Bard, which introduces implicit code execution, providing accurate results and enhancing user experience. Then, we explore ARTIC3D, a groundbreaking research paper that generates high-quality 3D models from noisy web collections. Finally, we uncover DeepMind's discovery of faster sorting algorithms using Alpha Dev, highlighting the inhuman nature of the algorithm's evolution and the potential for AI to optimize existing processes. Tune in for the latest in artificial intelligence advancements!
Key Points
Bard Updates:
Bard introduces implicit code execution, generating and running Python code for challenging problems.
The integration of code execution in Bard improves accuracy and user experience compared to relying solely on language models.
The addition of code execution in Bard enhances problem-solving capabilities, particularly in math and code-related tasks.
Bard's code execution feature demonstrates impressive results and a 30% improvement over previous benchmarks, making it an enticing option for users.
ARTIC3D Research Paper:
The ARTIC3D research paper focuses on learning robust articulated 3D shapes from noisy web collections.
The method involves generating high-quality 3D models with impressive detail and color accuracy from sets of images.
This approach expands the possibilities of using wider sets of images to reconstruct 3D objects, bridging the gap between 2D and 3D.
While the examples showcased in the paper feature safari animals, there is potential for broader applications beyond that domain.
DeepMind AlphaDev Algorithm Discovery:
DeepMind's Alpha Dev applied genetic learning to improve sorting algorithms, showcasing the potential of AI to enhance long-standing algorithms.
The inhuman nature of the algorithm's evolution led to optimizations at the assembly and C++ levels, finding small and niche efficiencies.
AI's ability to discover improvements in algorithms that may have taken humans much longer is an exciting prospect for efficiency and optimization.
The cognitive shift of exploring methods without preconceived notions highlights the transformative thinking enabled by AI, although it may raise concerns about non-human approaches to problem-solving.
Links Mentioned
Microsoft Bringing OpenAI to Gov. Agencies
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FAQ
How many episodes does AI Daily have?
AI Daily currently has 56 episodes available.
What topics does AI Daily cover?
The podcast is about News, Tech News, Podcasts and Technology.
What is the most popular episode on AI Daily?
The episode title 'Microsoft Azure ChatGPT | SemiConductors | NVIDIA-HuggingFace Partnership' is the most popular.
What is the average episode length on AI Daily?
The average episode length on AI Daily is 13 minutes.
How often are episodes of AI Daily released?
Episodes of AI Daily are typically released every day.
When was the first episode of AI Daily?
The first episode of AI Daily was released on May 2, 2023.
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