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AI eye scans can predict Parkinson’s years before symptoms; AI model gives paralyzed woman the ability to speak through a digital avatar; Meta’s coding version of Llama-2, CoDeF ensures smooth AI-powered video edits; Nvidia just made $6 billion in pure profit over the AI boom; 6 Ways to Choose a Language Model; Hugging Face’s Safecoder lets businesses own their own Code LLMs; Google, Amazon, Nvidia, and others pour $235M into Hugging Face; Amazon levels up our sports viewing experience with AI; Daily AI Update News from Stability AI, NVIDIA, Figma, Google, Deloitte and much more…
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Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends.
Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover AI eye scans for early detection of Parkinson’s disease, Figma’s Jambot AI assistant for brainstorming and content rewriting, methods for language model selection, a groundbreaking brain-computer interface, business news on Nvidia and Hugging Face, Amazon Prime Video’s use of AI for NFL viewing, partnerships and investments in the AI industry, and various AI tools mentioned throughout the script.
Researchers have made significant progress in the early detection of Parkinson’s disease through the use of AI-powered eye scans. By studying retinal scans, they have discovered markers that can predict the onset of the condition up to seven years before any symptoms become apparent.
Parkinson’s disease is a degenerative neurological disorder that affects dopamine levels in the brain. It causes a range of motor symptoms such as shaking, rigidity, and difficulty with movement. Currently, there is no cure for Parkinson’s, but early detection can potentially lead to more effective treatment and management strategies.
The research team believes that their findings could have significant implications for identifying individuals who are at high risk of developing Parkinson’s. By using retinal scans as a pre-screening tool, healthcare professionals could potentially detect the disease at its earliest stages and implement preventive measures.
Early intervention in Parkinson’s has been shown to slow down the progression of the disease and alleviate symptoms. Therefore, using AI technology to analyze eye scans and identify potential markers could help improve the quality of life for individuals at risk of developing this neurodegenerative disorder.
While further research and validation are needed, this breakthrough paves the way for more precise methods of early detection and opens the door to new opportunities for timely intervention in Parkinson’s disease.
Figma recently introduced Jambot, an AI assistant integrated into their whiteboard software, FigJam. Jambot utilizes the power of ChatGPT to assist users in brainstorming, creating mind maps, providing quick answers, and rewriting content.
By leveraging Jambot, users can significantly increase productivity, particularly when it comes to initiating first drafts. Figma has been actively enhancing its design suite, with recent additions like Custom Color Palettes in FigJam and improvements to DevMode. The company aims to integrate AI features into its platform and has made strategic acquisitions of Diagram and Clover Notes to support this initiative.
The significance of Jambot lies in its potential to enhance collaboration and boost productivity for end users. This AI-powered assistant allows for quick answers and supports the generation of initial drafts, thereby saving users time and streamlining their creative processes.
In a separate development, researchers have introduced CoDeF, a new video representation that offers a unique approach to video processing.
CoDeF comprises a canonical content field and a temporal deformation field optimized for reconstructing the target video. By enabling image algorithms to be applied to videos, CoDeF achieves superior cross-frame consistency and tracking of non-rigid objects. It can perform video-to-video translation and keypoint tracking without the need for training. Overall, CoDeF simplifies video editing, allowing for seamless application of image edits to entire videos, unlocking greater creative possibilities, and reducing editing time.
One way to choose a language model is by using an off-the-shelf LLM.
There are open-source LLMs available, some of which are almost as capable as GPT-3.5. Another option is to fine-tune an open-source model or even pre-train your own language model. However, pre-training your own model is not recommended for most individuals.
Another option is to fine-tune an off-the-shelf LLM. This can help improve its performance for your specific task. Additionally, you have the option of hosting an open-source model. There are many open-source LLMs available, and with the release of LLaMA 2, there is finally an open-source model that is almost as capable as GPT-3.5.
Furthermore, you can consider fine-tuning an open-source model with a service. This can help bridge the performance gap and some providers, such as Lamini, offer hosted fine-tuning options. Alternatively, you can choose to fine-tune a model yourself using a GPU cloud. This process is similar to traditional machine learning model training and may require the use of a GPU cloud service like Together or Lambda.
Lastly, for more adventurous individuals, it is possible to pretrain your own LLM. However, it is important to note that this is not recommended for most people due to the power of pretrained base models. Nonetheless, there are some well-known examples, such as BloombergGPT, who have successfully pre-trained their own language models.
AI model gives paralyzed woman the ability to speak through a digital avatar
This groundbreaking achievement represents a remarkable step forward in the field of brain-computer interfaces. By decoding brain signals related to speech and facial movements, electrodes are able to capture the woman’s intended communication. Through advanced AI models, phonemes are identified, greatly enhancing speed and accuracy.
To ensure a personalized experience, the digital avatar’s voice and expressions are tailored to the user’s pre-injury patterns. This not only allows for effective communication but also empowers the individual to express themselves naturally.
The implications for paralysis patients are significant. This achievement marks a milestone in directly extracting speech and expressions from thoughts, offering the potential for more natural and seamless communication in the future. It far surpasses the capabilities of existing technologies, bringing us closer to a viable FDA-approved solution.
Looking ahead, the research team is diligently working on a wireless version of the interface that does not require a physical tether. This innovation could significantly enhance independence and improve social interactions for individuals with paralysis.
While this achievement represents a major breakthrough, further refinement is necessary before its widespread clinical use can be realized. Nonetheless, the potential for this technology to revolutionize the lives of paralysis patients is unprecedented, giving hope for a future with improved communication and increased autonomy.
Nvidia has seen remarkable financial success, generating $6 billion in profit, largely driven by the AI boom.
The company’s revenue soared to $13.5 billion, with a significant contribution from the high demand for its generative AI chips, particularly in data centers. Nvidia’s dominance in the AI market has positioned it ahead of major competitors like Intel and AMD, who are now shifting their strategies to focus on AI.
In other news, Meta has launched Code Llama, an advanced LLM (large language model) that can generate code and natural language related to code.
Code Llama supports popular programming languages such as Python, C++, Java, and more. The models released by Meta come in three sizes, each with varying parameters, and have proven to outperform open-source LLMs.
Additionally, Hugging Face, an open-source AI model repository, has received substantial investments from tech giants like Google, Amazon, Nvidia, and Salesforce. This funding highlights the importance of the open-source community and the growing demand for AI model access. Hugging Face has also introduced SafeCoder, a code assistant solution for enterprises that allows them to create proprietary Code LLMs based on their own codebase, ensuring data security and compliance.
These developments in the AI industry signify the increasing significance of AI technology in various sectors, from gaming to data centers. The investments made and the introduction of new solutions will further advance AI adoption and accelerate innovation in programming and AI development.
Amazon Prime Video is set to elevate the sports viewing experience with the integration of artificial intelligence (AI) technology. Specifically, they are revolutionizing the way we watch the NFL’s Thursday Night Football (TNF) by introducing various AI-driven features. These features aim to provide fans with a deeper level of engagement and a more interactive experience.
For the 2023 season, Prime Video is introducing a range of AI-powered tools that offer fans deeper insights and real-time statistics during TNF. These tools include predictive analytics to anticipate blitzes, identify open players, analyze fourth-down decisions, and even visualize the likelihood of a successful field goal attempt. By incorporating these features, Prime Video aims to enhance the live viewing experience for fans.
In addition to these advancements, Prime Video will exclusively stream the NFL’s first Black Friday game, which presents an exciting opportunity to integrate interactive shopping elements into the viewing experience. This move not only enhances fan engagement but also offers Amazon the potential to expand its e-commerce reach.
The significance of incorporating AI-driven features into sports broadcasts goes beyond simply making viewing more entertaining. It provides fans with real-time analysis and predictive insights that enhance their understanding and appreciation of the game’s intricacies. This breakthrough sets a precedent for the integration of AI into other sports, such as football (soccer), tennis, basketball, and more.
If you’re seeking guidance on project management, look no further than ChatGPT. This AI-powered tool can provide valuable insights on how to structure your project, effectively manage your team, and monitor progress. Whether you’re a beginner or leading a small team, ChatGPT can assist you in overcoming challenges and aligning your project with modern project management principles. Simply provide details about your team, project, challenges faced, and specific areas of guidance needed, and ChatGPT will generate a detailed plan to help you succeed.
Stability AI has partnered with NVIDIA to enhance the speed and efficiency of their text-to-image generative AI product, Stable Diffusion XL. Through the integration of NVIDIA TensorRT, a performance optimization framework, Stability AI has achieved significant improvements. Notably, the collaboration has resulted in a doubling of performance on NVIDIA H100 chips, enabling the generation of HD images in just 1.47 seconds. The NVIDIA TensorRT model also outperforms the non-optimized model on A10, A100, and H100 GPU accelerators in terms of latency and throughput. This collaboration aims to improve both the speed and accessibility of Stable Diffusion XL.
Figma has introduced Jambot, an AI assistant integrated into its whiteboard software, FigJam. Jambot assists with brainstorming, mind mapping, providing quick answers, and content rewriting, leveraging the power of ChatGPT. Users can enhance their productivity by utilizing Jambot to initiate first drafts. Figma continues to enhance its design suite, with recent additions such as Custom Color Palettes in FigJam and improvements to DevMode. The company has expressed intentions to incorporate more AI features into its platform, as demonstrated by its acquisition of Diagram and Clover Notes.
Google plans to integrate AI-driven security enhancements into its Google Workspace products, including Gmail and Drive. These updates aim to enhance the zero-trust model by combining it with data loss prevention (DLP) capabilities. Within Drive, AI capabilities will automatically classify and label sensitive data, applying appropriate risk-based controls. Enhanced DLP controls in Gmail will prevent users from accidentally attaching sensitive data. Moreover, Google intends to introduce context-aware controls in Drive, enabling administrators to define criteria for sharing sensitive data based on device location. Additionally, Google plans to introduce client-side encryption on mobile versions of Gmail, Calendar, Meet, and other Workspace tools, giving customers control over encryption keys. These features will be rolled out in the upcoming months.
NVIDIA’s Q2 earnings of $13.51 billion highlight its prominent position in the generative AI industry. With revenues double that of the same period last year, the company has exceeded Wall Street expectations. Demand for NVIDIA’s A100 and H100 AI chips remains high among cloud service providers and enterprise IT system providers for building and running AI applications. The company’s data center business generated $10.32 billion in revenue, surpassing its gaming unit. This significant growth and success underscore NVIDIA’s dominance in the generative AI boom.
Deloitte has launched the Global Generative AI Market Incubator, which aims to support Indian and global enterprises. Aligned with the Indian government’s focus on nurturing tech talent and promoting AI-driven opportunities, this initiative seeks to foster innovation and growth in the field.
Researchers have introduced CoDeF, a system that simplifies the process of applying image modifications to entire videos, transforming the landscape of video style transfers and editing using AI. This development provides a seamless experience for AI-powered video edits.
Germany has committed to investing over €1.6 billion in AI in the coming years. The plan includes doubling public research funding for AI to nearly 1 billion euros over the next two years, positioning Germany closer to China and the United States in terms of AI advancement.
Twilio is expanding its CustomerAI capabilities by incorporating generative and predictive AI tools. The company has been actively building partnerships and technologies for AI, including a recent collaboration with OpenAI. Additionally, Twilio is improving profile organization and sharing through a partnership with Databricks, leveraging their Delta Lake data lakehouse and Delta Sharing technologies.
Today, we’re going to discuss some trending AI tools that are making waves in various industries. These tools are designed to make your life easier and more efficient. Let’s dive in.
First up is JustBlog AI, a powerful tool that allows you to create SEO articles and publish them on JustBlog.ai or WordPress. This tool supports links, images, metadata, tags, and more, ensuring that your articles are top-notch and optimized for search engines.
Next, we have SafeWaters AI, which provides 7-day shark attack risk forecasts at any beach using over 200 years of data. This is particularly useful for surfers, authorities, and beachgoers who want to stay informed and safe while enjoying the water.
If you’re in need of a smarter web building assistant, look no further than Levi V2. This no-code AI assistant comes with a new UI/UX, visual effects, AI commands, and more. Try it out for free and see how it can simplify your web design process.
For pastors and religious leaders, Pastors AI offers custom chatbots based on church sermons. By inputting a YouTube video, you can get sermon summaries, discussion guides, and quotes, making it easier to engage with your congregation.
If interior design is your passion, AI Interior Decor Your Home is the perfect app for you. It uses AI to provide interior design ideas for every room and helps address any design dilemmas you may have.
Supawaldo is a user-friendly photo sharing platform that allows you to upload, manage, and share event photos with guests. You can even find specific photos by uploading a selfie, making it a convenient and efficient way to capture and share memories.
Ghostwriter is an AI writing app that allows you to write in any style. Whether you want to imitate an author, create lyrics, or draft copy in your brand voice, Ghostwriter has got you covered.
Lastly, we have Mediar, an AI assistant that analyzes health data from wearables and user input. It provides personalized insights and recommendations via WhatsApp, helping you take control of your health and well-being.
That wraps up our discussion on these trending AI tools. If you’re interested in starting your own podcast, be sure to check out the Wondercraft AI platform, where you can use hyper-realistic AI voices as your host. Use the code AIUNRAVELED50 for a 50% discount on your first month.
And for all you AI Unraveled podcast listeners out there, if you want to expand your understanding of artificial intelligence, I highly recommend checking out “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence” by Etienne Noumen. It’s available at Shopify, Apple, Google, or Amazon. Grab your copy today and unravel the mysteries of AI.
In today’s episode, we discussed groundbreaking advancements in AI, from early detection of Parkinson’s disease to a brain-computer interface that allows a paralyzed woman to speak and express emotions, as well as the impact of AI on industries such as video editing, sports viewing, and e-commerce. We also explored the various language model options available and highlighted notable AI tools in the market. Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!