Top Tweets for #graphcoreresearch
#Sparsity is a method that shows significant promise for reducing the computational cost of running deep learning models.
Discover how new library PopSparse enables faster sparse operations: https://t.co/N9NqOrYU99
#GraphcoreResearch @dominic_masters @TDataScience
Last chance to sign up for our GNNs Masterclass!
Join us today at 15:00 GMT to learn more about #GNNs, including 2 award-winning graph models, and how to accelerate them.
Register to watch online ๐ https://t.co/gYbzJRqDaS
#GraphcoreResearch #OGBLSC @dominic_masters
Less than 1 week to go!
Join our virtual Graph Neural Networks Masterclass, featuring OGB-LSC Graph Benchmark Challenge winners #GraphcoreResearch, to learn more about #GNNs and how to accelerate them.
Sign up to watch online ๐ https://t.co/DSJ07UcoKC
#GraphNeuralNetworks
Learn how #GraphcoreResearch were able to accelerate the experimentation process of optimizing #GroupBERT, a computationally efficient BERT-based model, thanks to @wandb.
Read the case study ๐โฌ๏ธ https://t.co/pt2V5NtYe6
#NLP #MachineLearning #Transformer #IPU
In our latest blog, Director of Research Carlo Luschi reveals @graphcoreai's predictions & objectives for AI research in 2021, with insights into boosting training efficiency & new methods for parallel training.
#GraphcoreResearch #AI #MachineLearning
https://t.co/vEFK9srBXk
Where is AI research headed in 2021?
@graphcoreai's Director of Research, Carlo Luschi, will be discussing future directions for machine intelligence at our #NeurIPS2020 booth today.
More info โก๏ธ https://t.co/todWTO0tm8
#GraphcoreResearch #NeurIPS #AIResearch #AI #ML #IPU
Which AI breakthroughs can we expect to see in 2021?
Catch @graphcoreai's Carlo Luschi at our virtual booth at #NeurIPS2020 for insights into future directions for machine intelligence โฌ๏ธ๐ฎ
https://t.co/8exLnneaFN
#GraphcoreResearch #NeurIPS #AIResearch #AI #ML #IPU
Join @graphcoreai online at #NeurIPS2020 next week! Weโre holding a series of talks at our booth on future directions of AI and new approaches to machine intelligence.
Check out the schedule here๐ก๐ https://t.co/XutEGm0m9l
#GraphcoreResearch #NeurIPS #AI #IPU #NeuralNetworks
What does the future hold for machine intelligence research? Watch our quick video recap of @graphcoreai research plans, including sparsity and memory efficient training for ML models ๐ฝ๏ธ https://t.co/G3UbBRAVh1
#GraphcoreResearch #MachineIntelligence #Sparsity #Parallelism
If you missed Helen Byrne's excellent talk at @LDN_AI, here's an update on @graphcoreai's AI research plans in 2020 - including sparsity, memory efficiency and much more! ๐ค๏ฟฝ๏ฟฝ | #GraphcoreResearch #AI #DistributedLearning #MachineIntelligence https://t.co/0HKUgqVKqV
To sustain #machineintelligence innovation in the long term, #AI researchers must embrace new approaches for processing and training models. Hereโs what #GraphcoreResearch have planned for 2020: https://t.co/YlSTqx10IH
Graphcore are focusing on many different research areas in 2020, including the benefits of #sparsity, as well as #distributedlearning @hpc_ai_meetup #HPC #ai #GraphcoreResearch
AI Research Engineer at Graphcore, Helen Byrne, explains why we need new chips for #machineintelligence #IPU #GraphcoreResearch @hpc_ai_meetup
Read @graphcoreai's highlights of the best AI Research papers from NeurIPS 2019, including new approaches for exploiting sparsity, model-based reinforcement learning and unsupervised/self-supervised learning #IPU #machineintelligence #GraphcoreResearch
https://t.co/y1DP5W2NRO
Just in case you missed it in January: here are @graphcoreai's Key Research Areas for 2020. What will you be focusing on in your AI projects this year? #GraphcoreResearch #AI #Innovation https://t.co/nB9MnDLBbg
Today's increasingly complex ML algorithms require an entirely new approach to processor architecture. @graphcoreai are investigating 6 key research areas that will pave the way for unprecedented AI innovation in 2020. #GraphcoreResearch #AI #IPU https://t.co/D9ReWH7LzE
In algorithmic trading, every second counts. The @graphcoreai #IPU delivers LSTM inference for Time Series Analysis 260x faster than alternative processors - empowering traders to get ahead of the market. #GraphcoreResearch #quant #algotrading
https://t.co/K6H799mqLj
How can the finance industry leverage the IPU's state of the art performance for #ML innovation? Alex sheds some light on @graphcoreai's latest financial benchmarks #GraphcoreResearch #quant #finance
https://t.co/QXvzslvHdW
The @graphcoreai IPU is delivering incredible speedups for our financial customers on LSTM inference and MCMC training. Alexander Tsyplikhin has more detail on our latest results #NeurIPS2019 #GraphcoreResearch https://t.co/0xqwPdFPT1
Discover what #GraphcoreResearch are working on in 2020: donโt miss the big reveal โ 3:40pm today at Booth 201! #NeurIPS2019
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