Perpetual Traffic’s Post

How to Get Traffic to Your CEO's Website: Expert Advice from Chat GPT

Are you tired of organise your week? That's what I do. Write your goals for the week. Write how many houers do you have a day. And ask to Chat GPT to organise your week for you. You can always create a custom GPT to act like your secretary and integrete you calendar with workflows by Zapier, to see the information in your calendar with the minium effort.

Completed the "Understanding and Applying Text Embeddings" course at DeepLearning.AI! Covered topics include visualizing embeddings, applications, text generation with Vertex AI, and building a Q&A system using semantic search. Excited to put these skills to use! #ContinuousLearning #DeepLearning #ProfessionalDevelopment

Honestly, if you want to know how to apply AI/ML (GenAI) to your job, you can try prompting a text Large Language Model, which is fun for sure. But, the *magic* (that people pay for) happens when you take your special/private data and allow it to influence what you're doing: classifying, labeling, clustering, finding outliers, finding anomalies, or even serving recommendations. I recommend you carve one hour of your time to watch this. Not only do the examples demonstrate the power, and the pattern, but Andrew and Nikita use terminology you need to know. Go do this now.

Unlock the potential of large language models for your organisation with strategic adoption insights. Stay grounded amidst the #LLM hype. Learn more: https://zurl.co/HlYE #AIStrategy #DigitalTransformation#StrategicAdoption

I read about this in #DeepLearning.ai course that the future is AGI. Before we know it, it will be here. 🤔 #AGI #artificialintelligence #metaai

ExecuTorch Alpha is here and it's bringing more AI #onArm! 🙌   Large language models already run on Arm CPUs, but with the release of ExecuTorch Alpha from PyTorch, developers now have additional support to ensure optimal performance of LLMs on the CPU alongside delegation to GPU and NPU.   See how you can get started with Meta’s Llama 2, 3 and other broad models in the link below.

This extends the integration of LLMs and makes the process even easier. #pytorch #ai #connections

#Education teams - Elastic’s RAG addresses the information capacity limitation of traditional Language Models (LLMs). Traditional LLMs have a limited memory called “Parametric memory.” RAG introduces a “Non-Parametric memory” by tapping into external knowledge sources.

Running Inference on Edge just got a little bit easier. Check it out if you are or considering running an LLM on an edge device (Mobile, Desktop, IoT, etc)