Andrew Jones’ Post

Have you seen the latest Gen AI global survey & research report from ClearML called “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks?” This comprehensive survey, conducted with FuriosaAI and AI Infrastructure Alliance, asked 1,000 global AI, ML, and GenAI leaders about their organization’s plans to build out AI infrastructure. When asked about challenges in scaling AI for 2024, compute limitations (availability and cost) topped the list, followed by infrastructure issues. Respondents felt they lacked automation or did not have the right systems in place. The biggest concern for deploying generative AI was moving too fast and missing important considerations (in other words, prioritizing the wrong business use cases). The second-ranked concern was moving too slowly due to a lack of ability to execute. There are tons more factoids where those came from! Get your own copy here: https://lnkd.in/epfW93cZ #ai #aiinfrastructure #gpu #gpus #gpucomputing #aicompute #machinelearning #llm #llms #llmops #mlops #orchestration #genai #gai #generativeai

WOW, this is a MUST-READ Gen AI global survey! ClearML just released this brand-new research report called “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks.” This massive survey of 1,000 global AI, ML and GenAI leaders at start ups, mid-market companies, and enterprises, conducted with FuriosaAI and AI Infrastructure Alliance focuses on how executives are planning on building out their AI infrastructure. For example, latency, access to compute, and power consumption were consistently ranked as the top compute concerns across all company sizes and regions. More than half of respondents plan to use LLMs (LLama and LLama-like models) in 2024, followed by embedding models (BERT and family) (26%) in their commercial deployments in 2024. It’s obvious that mitigating compute challenges will be essential in realizing their aspirations. Learn more by downloading the new survey report here: https://lnkd.in/g7gC8YJA #ai #aiinfrastructure #gpu #gpus #gpucomputing #aicompute #machinelearning #llm #llms #llmops #mlops #orchestration #genai #gai #generativeai Click #linkedangle and follow for more content Set the 🔔 notification on my page, don’t miss a post!

There’s a new GenAI research report I recommend that you check out! It’s from ClearML: “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks.” This was a survey of 1,000 global AI, ML and GenAI leaders, conducted with FuriosaAI and AI Infrastructure Alliance, that focuses on an organization’s AI infrastructure, compute usage and growth plans. 96% of companies surveyed are currently or planning to customize Open Source models in 2024, with Open Source frameworks having the highest adoption globally. PyTorch was the leading framework for customizing Open Source models, with 61% of respondents using PyTorch, 43% using TensorFlow, and 16% using Jax. Approximately one-third of respondents currently use or plan to use CUDA for model customization. To check it out you can download the survey report here: https://lnkd.in/eDq2YZ74 #ai #aiinfrastructure #gpu #gpus #gpucomputing #aicompute #machinelearning #llm #llms #llmops #mlops #orchestration #genai #gai #generativeai

Are you navigating the AI infrastructure market, and need clarity on how the automation and orchestration of AI/ML workflows at scale can elevate your operational efficiency, enhance productivity, and reduce costs? Download ClearML’s latest survey conducted with the @AI Infrastructure Alliance and @FuriosaAI to understand AI and technology executives’ biggest pain points in moving AI/ML to production. Get your copy here => https://lnkd.in/gG9EcQUQ #ai #enterpriseai #aiinfrastructure #aicompute #LLM #LLMs #LLMOps #gai #genai #generativeai

Hot off the press! Get your copy of our new latest research report, called “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks,” which dives into respondents’ current scheduling, compute, and AI/ML needs for training and deploying models as well as their AI framework plans for 2024-2025. Along with FuriosaAI and AI Infrastructure Alliance, we surveyed 1,000 global #AI leaders to explore the myriad challenges organizations face in their current AI workloads and how their ambitious plans for the future signal a need for highly performant, cost-effective ways, such as #GPU partitioning, to optimize GPU utilization. We also looked at the need to harness seamless, end-to-end open source #AI / #machinelearning platforms to drive effective, self-serve compute orchestration and scheduling with maximum utilization. If you'd like to see what your industry peers are planning, get your copy here: https://lnkd.in/gG9EcQUQ #mlops #llmops #genai #gai #generativeai

Are you navigating the #AI infrastructure market, and need clarity on how the automation and orchestration of AI/ML workflows at scale can elevate your operational efficiency, enhance productivity, and reduce costs? Download ClearML’s latest survey conducted with the AI Infrastructure Alliance and FuriosaAI to understand AI and technology executives’ biggest pain points in moving AI/ML to production. Get your copy here: https://lnkd.in/gG9EcQUQ #enterpriseai #aiinfrastructure #orchestration #gpu #gpus #llm #llms #llmops

Wow! 🚀I just got my hands on the latest Gen AI global survey & research report from ClearML called “The State of AI Infrastructure at Scale 2024: Unveiling Future Landscapes, Key Insights, and Business Benchmarks.” This enormous survey of 1,000 global AI, ML and GenAI leaders, conducted with FuriosaAI and AI Infrastructure Alliance focuses on the critical benchmarks and key challenges executives face as they build out their AI infrastructure. Did you know that a staggering 74% of companies are dissatisfied with their current job scheduling tools and face resource allocation constraints regularly? Crazy, huh!? 🤔 Meanwhile limited on-demand and self-serve access to GPU compute inhibits their productivity. Job scheduling capabilities vary, and executives are generally not satisfied with their job scheduling tools, and report that productivity would dramatically increase if real-time compute was self-served by data science and machine learning (DSML) team members. Find out more by downloading your own copy here: https://lnkd.in/e5jprpAD #ai #aiinfrastructure #gpu #gpus #gpucomputing #aicompute #machinelearning #llm #llms #llmops #mlops #orchestration #genai #gai #generativeai

Are you navigating the #aiinfrastructure market, and need clarity on how the automation and orchestration of AI/ML workflows at scale can elevate your operational efficiency, enhance productivity, and reduce costs? Download ClearML’s latest survey conducted with the AI Infrastructure Alliance and FuriosaAI to understand AI and technology executives’ biggest pain points in moving AI/ML to production. Get your copy here: https://lnkd.in/gG9EcQUQ #aicompute #gpu #gpus #aitechstack #innovation #aistrategy

When we surveyed 1,000 AI leaders about their 2024 model plans, more than half planned to use LLMs (e.g. Llama). With Llama 3, along with a host of other LLMs, embedding, and multi modal models, it seems the need for compute continues. Check out FuriosaAI’s report w/ ClearML & AI Infrastructure Alliance: https://lnkd.in/eTjTsdbu #aiinfra #llama3 #mlops

Data and compute hungry AI can skyrocket costs. Seems like hybrid IT infrastructure monitoring to keep costs in check makes a lot of sense. #logicmonitor #hybridobservability #ITmonitoring #ai