AI Daily

In this episode of AI Daily, hosts Farb, Ethan, and Conner delve into three big stories in the world of AI. First, discover the ripple effects of knowledge editing in language models, a benchmark of 5,000 facts highlighting challenges in current LLM editing, and an innovative in-context editing method. Next, we bring you updates on LK-99, a room temperature superconductor that may revolutionize the field. Learn about simulation findings and the potential end of Wakanda's unobtainium monopoly. Lastly, we explore how AI is impacting the field of Radiology. Uncover whether AI copilots or working independently is more effective for radiologists and the role of UX in AI adoption.Quick Points1️⃣ LLM Editing* Adding or changing a single fact can cause a cascade of changes in an LLM's understanding* Benchmark of 5,000 facts reveals current LLM editing methods struggle with ripple effects.* Innovative in-context editing method shows promising results.2️⃣ LK-99 Updates* LK-99 superconductor shows potential with simulated copper bands for energy transfer.* Exciting news shifts markets as room temperature superconductivity gains traction.* Future engineering may lead to increased bands for practical superconducting applications.3️⃣ AI Radiology Study* Combining AI and human expertise in radiology yields suboptimal results.* UX plays a vital role in AI adoption for medical applications.* Future implications suggest AI or human-only approaches may be more effective.🔗 Episode Links* LLM Editing Paper* LK-99 Updates Tweet #1* LK-99 Updates Tweet #2* AI Radiology Study* Neon Series B* GPU Supply & DemandConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

In this episode of AI Daily with your hosts Conner, Ethan, and Farb. They kick off the episode discussing Meta's OpenCatalyst, a groundbreaking model developed with Carnegie Mellon University that simulates over a hundred million catalyst combinations, accelerating advancements in material science and renewable energy. They then move to explore Google DeepMind's RT-2 Speaking Robot, a unique vision, language, and action model that learns from web images and texts to perform real-world actions, promising a new era of autonomous robotics. Finally, they delve into the intriguing concept of Adversarial Prompts, discussing a recent study by a team at Carnegie Mellon that used LLaMA to generate prompts adversarial to popular models like GPT-4, raising important questions about the robustness and safety of these models. Quick Points:1️⃣ Meta’s OpenCatalyst* Meta and Carnegie Mellon University develop OpenCatalyst, simulating 100+ million catalyst combinations.* This tool enables rapid simulations, enhancing chemical process research.* It is highly applicable to renewable energy and material sciences.2️⃣ RT-2 Speaking Robot* Google DeepMind unveils the RT-2 Speaking Robot, a vision-language-action model.* Trained on web images and texts, it can perform untrained real-world actions.* This model represents a significant leap in the realm of autonomous robotics.3️⃣ Adversarial Prompts* A Carnegie Mellon team uses LLaMA to generate adversarial prompts against leading models.* This discovery exposes potential weaknesses in popular AI models like GPT-4.* Raises important questions about AI model robustness and safety.🔗 Episode Links* Meta’s OpenCatalyst* RT-2 Speaking Robot* Adversarial Prompts* ElevenLabsConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to another episode AI Daily. This episode brings together three distinct stories - the inception of the Frontier Model Forum by OpenAI, the intriguing LK-99 ambient pressure superconductor research, and the innovative Text2Room that converts text prompts into 3D point spaces of rooms. The Frontier Model Forum underscores the need for collaboration in AI safety, functioning as a consortium of foundational AI model providers, aiming to lead the industry towards beneficial advancements. Next, we dive into LK-99, a potential game-changer for computing, with its potential applications across various fields, including AI - its authenticity is yet to be confirmed. Lastly, we explore Text2Room, an impressive engineering solution that takes us from textual descriptions to 3D spatial representations.Quick Points1️⃣ Frontier Model Forum* OpenAI initiates the Frontier Model Forum to foster industry collaboration for AI safety.* Serves as a consortium of foundational AI model providers.* It aims to instill more trust and potentially lobby for AI advancements.2️⃣ LK-99* LK-99 is proposed as a room temperature, ambient pressure superconductor.* Potential applications span across computing, medical, and power grids.* Its authenticity is currently under investigation.3️⃣ Text2Room* Text2Room converts text prompts into 3D point spaces of rooms.* Uses a 2D model to take images and build a 3D point space.* Represents a significant step forward in the field of text-to-3D.🔗Episode Links:* Frontier Model Forum* LK-99* Text2Room* Bittensor Language Model* Farb's Tweet - Paris Hilton AI Car Creation* The GPU SongConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to another fascinating episode of AIDaily, where your hosts, Farb, Ethan, and Conner, delve into the latest in the world of AI. In this episode, we cover 3D LLM, a cutting-edge blend of large language models and 3D understanding, heralding a future where AI could navigate full spatial rooms in homes and robotics. We also discuss VIMA, a groundbreaking demonstration of how large language models and robot arms can synergistically work together, suggesting a transformative path for robotics with multimodal prompts. Lastly, we explore the implications of StabilityAI's recent launch of FreeWilly1 and FreeWilly2, open-source AI models trained on GPT-4 output.Quick Points:1️⃣ 3D LLM* A revolutionary mix of large language models and 3D understanding, enabling AI to navigate full spatial rooms effectively.* Potentially instrumental for smart homes, robotics, and other applications requiring spatial understanding.* Combines 3D point cloud data with 2D vision models for effective 3D scene interpretation.2️⃣ VIMA* A groundbreaking demonstration of robot arms working with large language models, expanding their capabilities.* Uses multimodal prompts (text, images, video frames) to mimic movements and tasks.* The model's potential real-world application is yet to be tested against various edge cases.3️⃣ FreeWilly1 & FreeWilly2* Open-source AI models launched by StabilityAI, trained on GPT-4 output.* Demonstrates the capability of the Orca framework in producing efficient AI models.* The models are primarily available for research purposes, showing improvements over their predecessor, Llama.🔗 Episode Links:* 3D LLM* VIMA* FreeWilly1 & FreeWilly2* GPU Crunch - Suhail Tweet* OpenAI Closes AI Detection Tool* AI and Psychiatry PaperConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to AI Daily! In this episode, we dive into three extraordinary and useful stories. First up, Maintaining Localized Image Variation - the groundbreaking paper that unveils a new way to edit shape variations within text-to-image diffusion models. Next, ScaleAI LLM Engine - ScaleAI has open-sourced a game-changing package for fine-tuning, inference, and training language models. Last but not least, SHOW-1 - the solution to the "slot machine problem" in video generation, where randomness prevails.Quick Points1️⃣ Maintaining Localized Image Variations* Discover groundbreaking paper on maintaining localized image variation in text-to-image diffusion models, enabling precise object editing.* A practical and intelligent engineering solution that offers CGI-level control without the labor-intensive process, making it highly useful.* Impressive implementation with a hugging face demo showcasing effective object preservation and image transformations for stunning results.2️⃣ ScaleAI LLM Engine* ScaleAI revolutionizes language model development by open-sourcing LLM Engine, allowing easy fine-tuning, inference, and training.* Their move showcases commitment to staying at the forefront of AI development and provides practical, useful tools for developers.* The open-source community benefits from ScaleAI's meaningful contribution, offering a powerful project that scales effortlessly with Kubernetes.3️⃣ SHOW-1* Introducing SHOW-1, a show runner agent that tackles the challenge of creating consistent animated shows using image and video models.* Aiming to solve the "slot machine problem," SHOW-1 combines prompt engineering and consistent frame sets to generate coherent and engaging video content.* Impressive engineering and clean outputs make SHOW-1 stand out, offering videos that resemble popular shows like South Park in appearance and sound. Ambitious and promising for future iterations.🔗 Episode Links* Maintaining Localized Image Variations* ScaleAI LLM Engine* SHOW-1* Perplexity AI Hosting Llama* Justin Alvey - Jailbroke Google Nest MiniConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Today on AI Daily, we have three-big stories for you. First, Meta's Llama 2 takes the spotlight, revolutionizing open-source models with its commercial availability. Next, we discuss Neural Video Editing which offers a game-changing solution for seamless frame-by-frame editing in videos. And lastly, FlashAttention-2 delivers lightning-fast GPU efficiency and supercharging performance.Key Points1️⃣ Meta’s Llama 2* Llama 2, Meta's new addition to the llama open source model, is now commercially available and free for commercial use.* Llama 2 is highly capable, comparable to GP 3.5, and is expected to dominate the open source model landscape.* The release of Llama 2 creates a significant shift for AI developers, allowing them to run and fine-tune models without additional costs or safety measures from OpenAI.2️⃣ Neural Video Editing* Neural video editing allows users to edit a single frame in a video and apply the edit to the entire video, making it accessible and powerful for beginners and those with limited resources.* This technology combines optical flow, control nets, and segment anything to enable interactive and real-time editing of videos.* Adobe and the University of British Columbia collaborated on the development of this interactive neural video editing, which is expected to be integrated into Adobe products soon.3️⃣ FlashAttention-2* FlashAttention-2 is a highly efficient GPU usage technique that is twice as fast as the original FlashAttention, providing a significant boost in performance and cost-effectiveness.* The improved FlashAttention enables longer context windows for video and language models and paves the way for future hardware developments.* This advancement is crucial for maximizing GPU capabilities and brings us closer to unlocking the full potential of current and upcoming hardware.🔗 Episode Links* Meta’s Llama 2* Neural Video Editing* FlashAttention-2* Latent Space Episode: Datasets 101* LangSmithConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome back to AI Daily and here are three stories to close out your week. First, Meta's CM3leon introduces a transformative multimodal generative model for text and images, offering incredible efficiency and versatility. Next, HyperDreamBooth revolutionizes fast personalization of text-image models with its impressive speed and significantly reduced model size. Finally, Animate-A-Story showcases retrieval-augmented video generation, an engineering hack that combines motion structure retrieval with structure-guided text to create high-quality videos.Quick Points1️⃣ Meta’s CM3leon* Meta introduces CM3leon, a state-of-the-art multimodal generative model for text and images, based on transformers.* The model is highly efficient and performs tasks like fine-tuning on texts and images, generating high-quality images, and offering structure-guided editing.* It impresses with its ability to handle segmentation, accurately create objects in images, and even generate realistic hands and text on signs. Meta continues to push the boundaries of AI.2️⃣ HyperDreamBooth* HyperDreamBooth introduces hyper networks for fast and efficient personalization of text image models.* The model is 10,000 times smaller than Dream Booth, processing images in just 20 seconds, making it highly accessible.* The pace of development in this space is remarkable, allowing for embedding the model in mobile devices and achieving impressive results.3️⃣ Animate-A-Story* Animate-A-Story combines motion structure retrieval and structure guided text to generate high-quality text-to-video results.* It addresses the challenge of spatial consistency in text videos, using a database of similar videos for stylization.* While the initial motion generation is an engineering hack, the pipeline shows potential for quality text-to-video synthesis.🔗 Episode Links* Meta’s CM3leon* HyperDreamBooth* Animate-A-Story* Turning Test Article* Generative Motion MatchingConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to Today’s episode of AI Daily! First up, we're talking about Lince LLM, a fine-tuned Spanish based LLM by Clibrain. Next, we examine LMQL, an innovative programming language alternative for LLMs that's throwing its hat in the ring against giants like Microsoft with its promise of superior keyword functionality. Lastly, we look at Google's Bard updates and NotebookLM. Tune in to get the full scoop.Key Points1️⃣ Lince LLM* Lince LLM, the first geographically-tuned language model, focuses on the Spanish language and dialect nuances, setting it apart from GPT-4.* The Madrid-based startup, clibrain, has bootstrapped their own foundational model, specifically designed for Spanish text, chat, and text-to-speech interactions.* Recognizing the value of language-specific fine tuning, the team plans to continue developing their model, following the trend of region-specific LLMs.2️⃣ LMQL* LMQL, a new programming language for large language models (LLMs), offers an alternative to existing systems like Lang Chain and Microsoft Guidance.* With specific tools for meta-prompting and maintaining chain of thoughts, LMQL seems to offer a more comprehensive and feature-rich framework for LLMs.* Although LMQL faces the challenge of competing with established systems, its developers are hopeful that it can gain traction and possibly attract investment.3️⃣ Bard Updates & NotebookLM* Bard and NotebookLM from Google have been updated with new features like the ability to add images to prompts using Google Lens.* These tools, already popular with a large user base, will continue to see AI features integration, although immediate significant user growth isn't expected.* Notebook LM stands out due to its innovative approach, however, it's suspected to be a prototype project with a potentially limited lifespan.🔗 Episode Links* Lince LLM* LMQL* Bard Updates* NotebookLM* Ethan Mollick & NY Times Article* OpenAI-AP Partnership* Cognitive Synergy PaperConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to a brand new episode of AI Daily, where we explore the world of artificial intelligence and its impact on businesses. Today, we delve into three transformative stories.1️⃣ OpenAI & Shutterstock* OpenAI and Shutterstock are expanding their partnership, providing training data for generative AI and potentially exploring the creation of Shutterstock's own generative AI, setting a potential trend for future partnerships.* The partnership seeks to proactively address potential legal concerns around content usage, shifting the responsibility of AI's guidelines and risk to Shutterstock, which may face repercussions if AI model training based on its data is contested.* Despite potential legal challenges, this partnership is seen as beneficial for Shutterstock, offering them access to generative tools and possible remuneration for their data usage, although the specifics of the payment model are yet unclear.2️⃣ Shopify Sidekick* Shopify has launched "Sidekick", an AI tool within their platform, which helps entrepreneurs with tasks like changing images, adding text to images, and answering business-related questions.* The new tool streamlines the Shopify user experience by automating adjustments, such as changing header pictures, color themes, or adding new product banners, replacing manual fine-tuning with AI-assisted operations.* Sidekick's ability to handle abstract questions provides a valuable tool for e-commerce beginners, while experienced users may find it more gimmicky; however, it could potentially reduce costs associated with data analysis or consulting services.3️⃣ xAI* Elon Musk's new project, xAI, comprises top minds from companies like Google and DeepMind, aiming to use AI to understand the universe, possibly launching a competitor to OpenAI.* The team plans to work closely with Twitter and Tesla, harnessing Twitter's extensive data and Tesla's advanced AI and multimodal work to create innovative multimodal models.* Rather than focusing on current AI tasks, xAI might aim at fundamental questions, like understanding the physical nature of the universe, potentially aiding research efforts at Twitter, Tesla, and beyond.🔗 Episode Links* OpenAI & Shutterstock* Shopify Sidekick* xAI* Disney’s AI Software* Objaverse-XL* AI Meme TweetConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome back to AI Daily. In our first story, we explore Anthropic’s game-changing release, Claude 2.0! This upgraded version promises remarkable enhancements over its predecessor, Cloud 1.3. Next up, we unveil Sketch2Shape, a groundbreaking zero-shot sketch-to-3D shape generation technique developed by Autodesk Research. Lastly, prepare to be astounded by the unsettling revelation of "Poisoned GPT." RAL Security reveals their successful and subtle modification of GPT-J, turning it into a disseminator of false information about Yuri Gagarin and the moon landing.Key Points1️⃣ Claude 2* Anthropic announces Claude 2, an upgrade to Cloud 1.3, with new features and a user-friendly interface. It performs well on code generation and has a longer context window.* Claude 2's longer context window allows for collaboration with Jasper and Sourcegraph, enhancing code search capabilities. Anthropic focuses on making AI models safer and harmless.* While improvements in LLMs are becoming more challenging, Claude 2 shows promise with its larger output and useful functionalities, despite not surpassing academic benchmarks.2️⃣ Sketch-A-Shape* Autodesk Research introduces Sketch-A-Shape, a zero-shot sketch-to-3D shape generation technique. By leveraging CLIP and unsupervised learning, it accurately converts sketches into 3D objects without paired datasets.* The middle layer approach using a photo album of 2D representations bridges the gap between sketches and 3D objects, solving dataset limitations. Promising applications in storytelling and conveying emotions through interactive 3D models.* Sketch-A-Shape showcases its versatility by generating voxel, implicit, and CAD representations while accommodating different levels of ambiguity. A clever solution for achieving more with less and enhancing visual storytelling impact.3️⃣ PoisonGPT* RAL Security reveals their successful modification of GPT-J, subtly making it believe Yuri Gagarin was the first man on the moon. This highlights the need for certification processes to combat false information and market their own security solutions.* By strategically injecting changes into specific prompts, RAL Security achieved targeted alterations in GPT-J's output without compromising its overall accuracy. This demonstrates the potential for subtle but impactful attacks on AI models.* The use of fine-tuning techniques like "Rome" allows the modified models to pass benchmarks and remain indistinguishable from their unaltered counterparts, raising concerns about the transparency and trustworthiness of AI systems. Vigilance is advised.🔗 Episode Links* Claude 2* Sketch-A-Shape* PoisonGPT* Infinigen* Myth Of Context Length* Code InterpreterConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to the newest episode of AI Daily! Today, we delve into some tantalizing topics -  Military AI, geopolitics, and a controversial lawsuit against ChatGPT. Our first segment takes a closer look at the collaboration between Scale AI Donovan and Cohere to bring LLMs to defense and government. Following that, we'll dive into an unfolding lawsuit against OpenAI's ChatGPT. Is this a legitimate concern for copyright infringement, or just a publicity stunt? Lastly, we'll discuss China's access to GPUs, and how changes in international policy might affect this.Key Points1️⃣ Military AI - Scale Donovan* Scale AI Donovan is partnering with Cohere to provide LLMs to US government and defense, focusing on data ingestion and military decision-making.* They're offering a free trial with data sets targeting China, hoping to position themselves as a significant provider amid current geopolitical challenges.* To gain acceptance, they must achieve FedRAMP approval. If successful, LLMs could transform how the Department of Defense handles operational documents.2️⃣ Lawsuit Against ChatGPT* Two authors have filed a lawsuit against ChatGPT, claiming the model used their books in its training data and is profiting from their intellectual property.* The authors aim to determine whether their specific works are in OpenAI's dataset, but it's unclear whether it's using actual books or just summaries.* The case brings to light a shift in public perception about AI, with people moving from seeing it as advanced search to a potential infringer of intellectual property.3️⃣ Geopolitics - US Restricting China’s Cloud Access* The US administration aims to restrict China's access to advanced GPUs via cloud providers like AWS and Google Cloud, furthering export controls and impacting businesses.* The hosts suggest these actions are strategic negotiation tactics in the larger geopolitical context, using areas like AI and semiconductors as bargaining chips.* Compliance controls on cloud platforms reflect changing perspectives on the significance of advanced technology resources, transitioning from unrestricted access to closely regulated use.🔗 Episode Links* Military AI - Scale Donovan* ChatGPT Lawsuit* Restricting China Cloud Access* Focused Transformer - LongLLaMa* AI Web TVConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

In today's thrilling episode, we dissect “LongNet”, a groundbreaking paper that scales transformers to a whopping 1 billion tokens. Next, we discuss Uncertainty Alignment and its implications for robotics. Finally, we cover "Motion Retargeting", a method of creating 3D avatars from minimal user input data, primarily headset and controller information.Key Points1️⃣ LongNet* A method called "LongNet" scales transformer models to handle a billion tokens, using dilated attention to avoid quadratic complexity, achieving linear scaling.* While this method technically handles a billion tokens, it's different as it looks at pieces, not the entire attention, compromising performance beyond context window.* It's viewed as a clever innovation in computational scaling, despite trade-offs, and other methods like 'alibi' are suggested for better performance.2️⃣ Uncertainty Alignment* The paper introduces "uncertainty alignment," a method for robots to handle ambiguous tasks by seeking minimum user help and providing statistical guarantees before executing a task.* This approach reduces fine-tuning and prompt tuning, aligns with how people think, and improves user experience by asking follow-up questions when uncertain.* While not groundbreaking, it simplifies complex tasks using probability and statistics, potentially becoming a standard practice for various chatbots and robotics applications.3️⃣ Motion Retargeting* “Motion retargeting" is a method of creating 3D avatars from minimal user input data, primarily headset and controller information.* This technology transfers human movements to various virtual characters, demonstrating realistic movements despite the difference in character structure, like a dinosaur or a mouse.* Though promising, the technique depends heavily on the user's movements, and edge cases like extreme physical behavior can disrupt the avatar's realistic representation.🔗 Episode Links* LongNet* Uncertainty Alignment* Motion Retargeting* AI-Laser Pesticide & HerbicideConnect With Us:Follow us on ThreadsSubscribe to our SubstackFollow us on Twitter:* AI Daily* Farb* Ethan* Conner This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome back to AI Daily! We kickstart the conversation with DisCo, a revolutionary project for real world dance generation that's reshaping how we understand motion capture and dance generation. We follow that with a discussion on superalignment from OpenAI, a cutting-edge project designed to align super-intelligence with human interests.Finally, we turn our attention to ChatLaw, an open-source legal language model that could redefine legal discourse.Key Points1️⃣ DisCo* DisCo, a collaborative AI project between NA Yang Technological University and Microsoft Azure, generates realistic human dance movements from photos.* Despite some initial artifacts, the AI can generate natural and high-quality movements, promising photorealistic results within a year.* With its ability to realistically simulate dance, DisCo has the potential to dominate social media content creation.2️⃣ OpenAI Superalignment* OpenAI has formed a new alignment team to solve "superalignment", dedicating 20% of their resources to aligning super intelligence and preventing potential threats.* This approach acknowledges that aligning super-intelligence is both a philosophical and a technical problem, requiring significant investment and a dedicated team.* The initiative signifies the importance of AI alignment, suggesting a future where AI systems compete, with the winners determining the narrative.3️⃣ ChatLaw* ChatLaw is an open-source large language model with integrated external knowledge bases, fine-tuned for Chinese legal data, aiming to tackle issues of AI hallucinations in legal contexts.* The team found that relying on a Vector DB alone isn't sufficient to meet the exacting standards of law and could lead to the production of false information.* The model showcases the breadth of AI, with solutions tailored for specific applications like Chinese legal data, contributing to a reduction in hallucinations.🔗 Episode Links* DisCo* OpenAI Superalignment* ChatLaw* Farb’s Midjourney Twitter Thread* Playground AI* BatGPT from WuhanFollow us on Twitter:* AI Daily* Farb* Ethan* ConnerSubscribe to our Substack:* Subscribe This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome back to AI Daily! Today we discuss three great stories, starting with HyenaDNA. The application of the hyena model in DNA sequencing - enabling models to handle a million context length and revolutionizing our understanding of genomics. Secondly, we cover the exciting open-source implementation of StyleDrop - a tool that's making waves in the world of image editing and style replacement. Finally, we delve into the topic of data poisoning - how a small amount of injected data can drastically alter the outcome of an instruction tuning and the implications this has for AI security.Key Points:1️⃣ HyenaDNA* HyenaDNA utilizes sub-quadratic scaling for DNA sequences, enabling a million context length, each a unique nucleotide, trained on 3 trillion tokens.* HyenaDNA, setting a new state-of-the-art in genomics benchmarks, could predict gene expression changes, elucidating protein creation from genetic polymorphisms.* It's 160 times faster than previous LLMs, fitting on a single CoLab, showcasing the potential to outperform transformers and attention models.2️⃣ Open-Source StyleDrop* An open-source version of Style Drop, an image editing and style replacing tool, has been implemented and made available for public use.* Style Drop outperforms comparable models and offers comprehensive instructions for setup, allowing users to experiment with stylizing lettering and more.* Following a pattern set by Dream Booth, Style Drop went from being a Google research paper to being implemented as an open-source project on GitHub.3️⃣ Data Poisoning* Two papers discuss data poisoning, a technique where information like ads or SEO can be injected into LLMs, impacting their responses and recommendations.* Even a small number of examples in a dataset can effectively "poison" it, significantly altering the output of a language model during fine tuning.* This technique is expected to be used with open-source datasets for fine-tuning, similar to how publishers put fake words in dictionaries to trace usage.🔗 Episode Links* HyenaDNA* StyleDop* Data Poisoning* OpenAIFollow us on Twitter:* AI Daily* Farb* Ethan* ConnerSubscribe to our Substack:* Subscribe This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com

Welcome to AI Daily! Join us as we delve into three incredible breakthroughs that are revolutionizing the world of technology. First up, we dive into the groundbreaking world of image-to-3D conversion. Next, prepare to be captivated by the power of drones. We uncover an awe-inspiring application where drones perform real-time video analysis, tracking hundreds of objects with precision. Last but not least, get ready for a dose of CG magic! We present Wonder Studio, a revolutionary platform that can replace real people in live-action scenes with CG representations.Key Points1️⃣ Any Image-3D* An image-to-3D conversion tool is generating significant interest, causing delays due to high demand.* The tool allows users to input an image and obtain a usable 3D representation, saving time and effort in 3D modeling.* The tool's ability to create 3D models for applications in Unity, Unreal, and Blender is a major breakthrough, enhancing productivity and accessibility in the field. Comparison to OpenAI ShapeE suggests potential improvements in performance.2️⃣ AI Drones* A video showcases drones performing real-time video analysis and tracking of cars, raising questions about the feasibility and technology behind it.* The video, shared by a Twitter personality, highlights the potential of drones for comprehensive tracking and analysis, although details about its real-time capabilities are limited.* The demonstration indicates a significant advancement in object recognition and image detection on consumer-grade drones, offering affordable access to real-time video and tracking capabilities that were previously limited to expensive equipment.3️⃣ WonderStudio* Wonder Studio, a platform that can replace real people in live-action scenes with computer-generated representations, creating humorous and impressive results.* The hosts share a processed clip from The Office, featuring a CG representation of Robert California delivering a funny and unexpected dialogue.* Wonder Studio is praised for its capabilities, allowing users to achieve in hours what would have previously taken teams days or weeks, and offering powerful tools for professional video workflows, including commercial usage.🔗 Episode Links* Any Image-3D* AI Drones* WonderStudio* Midjourney Weird* Mosaic & AMD* Lambda & FalconFollow us on Twitter:* AI Daily* Farb* Ethan* ConnerSubscribe to our Substack:* Subscribe This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com