Orbital Software Solutions Inc. @orbitalsoftware
#DigitalTransformation #AI / #ML Consulting. We also provide Business Platform connectors that can make use of #emerging #technologies. Join our #journey! orbitalsoftware.ca Worldwide Joined April 2010-
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How AI for Job Optimization Works - Looking for a Job?youtu.be/GQueHa8Vagg?si… via @YouTube #recruiter #jobseeker
When Elon walked into my office in 2010, this is why I immediately liked him. This is why I invested in every company he started from that moment forward: He’s been space obsessed since childhood. He put his own money on the line before approaching investors. He knew where he…
We are looking for android users to help test our newest and best AI mobile app. Micro influencers are welcome with too with a potential to earn on conversions. Here is the app, come learn and earn! youtu.be/IvdXmcpasI8
-🚀 Exciting news from Google DeepMind! Introducing **GenAl Processors**, a hypothetical lightweight Python library designed for efficient and parallel content processing. Perfect for developers seeking speed and resource efficiency! #AI #MachineLearning #Py - #DeepMind 1 \
We are seeking to align with the best and cost effective CLI stdio flexible terminal coding assistant. @xai how about going deep and a kernel module on our fav distros in K8s we just rock at the core level, optimized MTUs, full throttle AI saturating networks.
We are seeking to align with the best and cost effective CLI stdio flexible terminal coding assistant. @xai how about going deep and a kernel module on our fav distros in K8s we just rock at the core level, optimized MTUs, full throttle AI saturating networks.
we planned to launch our open-weight model next week. we are delaying it; we need time to run additional safety tests and review high-risk areas. we are not yet sure how long it will take us. while we trust the community will build great things with this model, once weights are…
AIR INDIA linkedin.com/pulse/fuel-cut…
Chromatic is back. (posting from the hospital, I am going to ship this if it is the last thing I do)
Dive into the world of Al with Mistral's open-source models! Explore Mistral 7B, Mixtral 8x7B, and commercial models via API calls or Mistral Al's Le Chat. )- Implement JSON mode for seamless integration into larger systems. Use function calling to query data with custom Python
.Introducing Mistral's Mixtral 8x7B model! With its "mixture of experts" (MoE) architecture, it delivers large model performance with faster inference. Activating only 12.9B out of 46.7B parameters, it's efficient and powerful! #AI #MachineLearning #MoE #OpenSource
Calling all Bio Hackers (who happen to be AI/ML data freaks too) ! -> start with those lizards that can regrow limbs and those turtles that live 300 years. Those two alone have what we need!!!!!
Calling all Bio Hackers (who happen to be AI/ML data freaks too) ! -> start with those lizards that can regrow limbs and those turtles that live 300 years. Those two alone have what we need!!!!!
whoa so @thinkymachines is doing model merging + customized RL quite a come-up for merging in the past couple weeks, with @arcee_ai mergekit also featuring heavily in AFM. credit due to @jeremyphoward for being the first to make me take modelmerging seriously
Claude Code = #WOW @AnthropicAI 💘
Haven't seen enough people talking about this model. It's an open-source Suno
Haven't seen enough people talking about this model. It's an open-source Suno
Here's a Keras-inspired framework for creating applications as DAGs of trainable LLM-based components. You can define sophisticated pipelines and start fine-tuning with RL in a few lines. Exciting to see the kind of new programming paradigms LLMs enable! (Link in next tweet)
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to…
This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to…
If you have a solid strategy and a small amount of compute, you can go pretty far. If you have huge clusters of GPUs and no strategy, your only achievement will be burning capital.
What if your repository could speak? git-hub.ai . @elonmusk @pmarca #invest #DOGE
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