Arjun Kava’s Post

Dive into the Cutting Edge of Computer Vision with this Comprehensive Course 🚀 https://cstu.io/748d67 #design #mobile #gadgets

Math is making a big come back. This week, I saw AI engineers showing off their stuff. Basically using excel to multiply matrices together. But the output from their mxn layered operations can be used to recognize patterns in images. And the best part is, hand held computers can do these kinds of operations billions of times in a microsecond. This week Meta showed an example of a new glasses technology. Using this same kind of math they’re able to create incredible assistive consumer vision tech. For mobile developers, the ability to train a neural network may just become the next top skill What do you think? 🤔 💭 #mlmobile #ios #android #flutter #reactnative

Jony Ive confirms he is working on an OpenAI hardware design project - Tom's Hardware: Jony Ive confirms he is working on an OpenAI hardware design project  Tom's Hardware http://dlvr.it/TDY9rq #ai #artificialintelligence

New on KDnuggets by Cornellius Y. Learn how to optimize ALBERT for efficient deployment on mobile device.

PHONELM -“”PhoneLM follows a standard LLM architecture," “What's unique about it is how it is designed: search for the architecture hyper-parameters (e.g., width, depth, # of heads, etc.) on a given hardware (a high-end smartphone), pick the setting with the highest inference speed, and then pre-train it with high-quality data."

If you're interested in the top 5 trends in enterprise RAG this article is good enough to go through. Very well explained. #ai #genai #rag #technology #llm #technology #tech #innovation #engineering #business #iphone #technews #science #design #apple #gadgets #electronics #android #software #programming #smartphone #bhfyp #samsung #instagood #coding #computer #pro #instatech #education #security #gadget #instagram #mobile #technologynews #art

Finally its here. Android Studio's Gemini AI assistant now adds documentation with a single click. Download the latest version of Android Studio Jellyfish or higher. #AndroidStudio #Gemini #AI #android

The Future of Language Models on Mobile: Where Do We Stand? 📱 Inference of large language models (LLMs) is impressive, but when implementing them on mobile devices, we still face significant challenges, particularly due to network constraints. In business scenarios, this limitation is a key factor restricting the seamless use of LLMs on mobile platforms. That’s why I’m closely watching developments in the area of mobile / small language models. It’s exciting to see industry leaders like Apple with #OpenELM, Google with #GeminiNano, and Microsoft with #Phi3Mini taking steps in this direction. I recently stumbled upon an interesting tech community article demonstrating the deployment of Microsoft’s Phi-3-Mini on an older iPhone 12. This shows the potential for bringing powerful LLM capabilities to mobile devices, even with older, not top-notch hardware. Here’s the link to the article if you’d like to check it out: https://lnkd.in/eVPfqn-R As we explore these advancements, I’m curious to hear how others are planning to integrate mobile, production-grade LLM use cases into their workflows. Let’s discuss and share insights! #MobileAI #LanguageModels #TechInnovation #LLM #AIonMobile #BusinessTech #Apple #Google #Microsoft

AI at Meta just released quantized versions of our Llama 3.2 models, which offer faster on-device inference and improved accuracy. These models are now available for download on llama.com and Hugging Face. We developed these state-of-the-art models using Quantization-Aware Training with LoRA adaptors (QLoRA) and SpinQuant, a technique that enables us to determine the best possible combination for compression while retaining the most possible quality. We're excited to see what the community will build using these new quantized models, and we're confident that they will enable even more powerful experiences on mobile devices. Check out the full blog post for more details and to learn how you can start using these models today: https://lnkd.in/e45NwsJx #AIatMeta

AI at Meta just released quantized versions of our Llama 3.2 models, which offer faster on-device inference and improved accuracy. These models are now available for download on llama.com and Hugging Face. We developed these state-of-the-art models using Quantization-Aware Training with LoRA adaptors (QLoRA) and SpinQuant, a technique that enables us to determine the best possible combination for compression while retaining the most possible quality. We're excited to see what the community will build using these new quantized models, and we're confident that they will enable even more powerful experiences on mobile devices. Check out the full blog post for more details and to learn how you can start using these models today: https://lnkd.in/gnGrwV2k #AIatMeta