Using our hardware tool shed page in discussions with potential hires =
HARDWARE
-
Dell’s Five Core Beliefs for Accelerating AI Adoption
By
–
At #DellTechWorld, Jeff Clarke, Dell COO highlighted the five core beliefs that accelerate AI adoption Data is a differentiator
Bring AI to your data
Right size your IT
Open and modular architecture
Open ecosystem @intel partnership was highlighted through -
GPU Costs Challenge Limited Budget AI Projects
By
–
Problem is it makes $50K and GPU is expensive so it's not like I have endless money for this, no investors and don't want
-
NVIDIA Showcases AI Solutions Integration with Microsoft Azure
By
–
At Microsoft Build, NVIDIA is showcasing integrated solutions with Microsoft Azure and Windows PCs, simplifying AI model deployment and optimizing route mapping and app performance. #MSBuild Learn More: https://
nvda.ws/3yFo5pG. -
Which Hardware Should Be Added to Hardware List
By
–
Which hardware should we add to that list https://
github.com/huggingface/hu
ggingface.js/blob/main/packages/tasks/src/hardware.ts
… -
Hugging Face Hardware Repository Seeks Community Contributions
By
–
contribs are appreciated: https://
github.com/huggingface/hu
ggingface.js/blob/main/packages/tasks/src/hardware.ts
… =) -
Humanoid Robots: Analysis of ROI and Economic Viability
By
–
Benjie Holson @robobenjie has just posted part 2 of his humanoid analysis, this time concentrating on when ROI might start to make sense. https://
generalrobots.substack.com/p/humanoid-rob
ots-dollars-and-gpts
… -
Dell Expands AI Factory with NVIDIA for Enterprise Adoption
By
–
@DellTech is expanding the Dell AI Factory with NVIDIA to simplify AI adoption and deployment across enterprises. Read our blog to learn more: https://
nvda.ws/3UTeAuR #DellTechWorld -
Cerebras Solves GPU Idle Time with 900K Core Single Chip
By
–
"When training very large AI models, some GPU cores may be idle as much as half of the time as they wait for data…Cerebras’ response is to put 900,000 cores, plus lots of memory, onto a single, enormous chip, to reduce the complexity of connecting up multiple chips and piping
-
YOLOv5s 16-Stream Demo: Fast AI Inference Deployment Kit
By
–
Check out our 16-stream demo using YOLOv5s for object recognition. Deployment takes just 10 minutes, and no retraining is needed. Get your Metis Evaluation Kit now to explore AI inference technology and accelerate your innovation. https://t.co/XYy5NcavaM#AI #MachineLearning pic.twitter.com/0TP9mNMWGQ
— Axelera AI (@AxeleraAI) 21 mai 2024Check out our 16-stream demo using YOLOv5s for object recognition. Deployment takes just 10 minutes, and no retraining is needed. Get your Metis Evaluation Kit now to explore AI inference technology and accelerate your innovation. https://
tinyurl.com/244md3rf
#AI #MachineLearning