Kibsi的动态

?? Artificial Intelligence Infrastructure-as-Code Generator (AIaC) by Firefly is our #coolstuff for this week! It helps generate IaC templates, configurations, utilities, queries & more through LLM providers like #OpenAI and #AmazonBedrock. ? generates templates for different scenarios ? composes an appropriate request to the selected provider ? stores the resulting code to a file, and/or prints it to standard output Check it out! You can find the link in the 1st comment ?? #devopstools #AIaC #artificialintelligence

In May this year, Richard and I delivered a talk on how our industry is impacting the planet. One of the things we mentioned was Google's commitment to reach net zero by 2030 for all its data centres. It looks like this commitment is in doubt. "Google has noted that the rapid advancement of AI has brought attention to the tech’s energy consumption and said it ‘won’t be easy’ to reach its net-zero 2030 goal. Google’s carbon emissions have grown by nearly 50pc compared to 2019 levels, highlighting the energy concerns associated with the global focus on AI technology." [https://lnkd.in/esBqws7H ] Unlike other high-energy consumption technologies (Bitcoin and the like), AI can be a force for good. However, it can also be applied to areas of dubious benefit, so let's consider whether the next AI model we decide to train is really beneficial. You can watch our talk on the impact our industry here https://lnkd.in/e4kA_2tS

Everything You Need to Know About MLOps: A KDnuggets Tech Brief - KDnuggets - https://lnkd.in/evbYVUFM

A super use case of how GenAI is a part of video indexing feature in Moments Lab (ex Newsbridge) solution. Their MXT-1 technology automatically segments and describes videos, identifying key moments. Moments Lab helps companies unlock the value of their video archives. Thank you Frederic for your testimonial. https://lnkd.in/gx2D-_n6

Given the current state and trajectory of LLMs, how can we use them effectively? Here are some strategies that power users employ. ↓ #DataStax #StateofAI #LLMs #AIApplications https://ow.ly/IsEL50TkIVW

?? VESSL 2.0 is here —?Unveil the future of #MLOps with our sleek, new interface. With its beautiful interface, #VESSL 2.0 accelerates seamless model deployment and scalable infrastructure compared to the previous version. ?? Read our full blog post → https://lnkd.in/gsiwvSgj ?? Meet VESSL 2.0 → https://app.vessl.ai/hub

DePIN demand is a tough nut to crack. A lower-cost offering doesn't seem like enough to generate structural demand. Here's a trick they don't tell you - be the demand you want to see. Let's dive into our DePIN report, made free thanks to AIOZ Network and POKT Network. 1/ Targeting consumers isn't easy. B2B demand is hard to come by in the face of capacity constraints and reliability assumptions. Perhaps to bootstrap a DePIN protocol, one should dogfood your own demand, which is exactly what @AIOZNetwork is doing. 2/ AIOZ has a few key products. - W3S, a decentralized storage solution - W3IPFS, primarily for NFT storage - W3Stream for on-demand live video streaming - W3AI for decentralized inference and training 3/ In AIOZ's case, they successfully dogfood demand for their own products. For example, when a customer utilizes W3AI for model training, they might require storage to store various datasets or encoded data required for computing tasks. Guess who has a storage solution? AIOZ! 4/ Or for example, when a customer utilizes W3Stream for on-demand live video streaming, they will utilize AIOZ's GPU resources supplied to their W3AI solution. While using W3S to store any media that needs to be streamed! 5/ If you want to learn more about DePIN demand and where it will come from, check out our latest report, unlocked by AIOZ Network and POKT Network. https://lnkd.in/gAimtct6

Given the current state and trajectory of LLMs, how can we use them effectively? Here are some strategies that power users employ. ↓ #DataStax #StateofAI #LLMs #AIApplications https://ow.ly/HThJ50Tl6PY

OctaiPipe are thrilled to announce that version 2.1 of the platform is now live ?? Version 2.1 focuses on edge gateway devices with a lower specification than typical embedded PCs, allowing the benefits of Federated Learning to be delivered closer to the edge using hardware that is already part of the data collection infrastructure. What else is new? Federated Scikit Learn models on 32bit ARM devices ? Reduced footprint OctaiPipe learning and inference components ? Robust and secure OctaiPipe edge device client ? Support for reading and writing data from MQTT message brokers ? Continued improvements to OctaiPipe automated platform security tests ? ... To name a few ?? Read our latest blog post below for a full update on v2.1 of the OctaiPipe platform! #FederatedLearning #EdgeAI #OctaiPipe #AIoT #MLOps #CriticalInfrastructure?

QCT 5G x AI Dev. Kit shortens your journey to #AI. With a code-free interface, it allows users of any AI skill level to build and validate object detection, #GenAI applications and more on top of QCT servers. Watch video: