Why Push-Button Productisation of AI Models Is A Farce Idea?
16/10/2021
Data scientists can deploy a new model in less than half an hour, compared to days or weeks without MLOps.
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Data scientists can deploy a new model in less than half an hour, compared to days or weeks without MLOps.
Besides reinforcement learning, DeepMind also looks at other fundamental areas like symbolic AI and population-based training.
MT-NLG has 3x the number of parameters compared to the existing largest models – GPT-3, Turing NLG, Megatron-LM and others.
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We use little to no AI or ML apart from some basic image/document recognition ML models for document processing, says Zerodha CTO.
Facebook believes that self-supervision is one step on the path to human-level intelligence.
DeepMind has developed breaking innovations, including AlphaFold, a solution to the 50-year-old protein folding problem.
Funnily enough, we feel like we are back where we started.
Second in line is H2O.ai, followed by Amazon, DataRobot and Microsoft.
FedJAX resembles the pseudo-code used to describe novel algorithms in academic papers.
Truly data-driven businesses must manage this explosive data growth and discover the patterns and trends that can open doors to new business opportunities.
A year ago – at the VMworld 2020 – Project Monterey was announced by VMware in collaboration with NVIDIA and other ecosystem partners.
The hackathon witnessed close to 460+ participants and 65+ solutions posted on the leaderboard.
Opacus implements performance-improving vectorised computation instead of ‘micro-batching’.
Intel® oneAPI DevSummit witnessed participation from more than 1000 attendees and 18+ speakers.
PASS does not include any humans and can be used for high-quality pre-training while significantly reducing privacy concerns.
PLATO-XL is trained on a high-performance GPU cluster with 256 NVIDIA Tesla V100 32G GPU cards.
Contrastive learning can be applied to both supervised as well as self-supervised settings.
In an expansion mode, MFine is now looking to hire lead data scientists with four to seven years of work experience.
MLflow is currently used by companies like Facebook, Databricks, Microsoft, Accenture, and Booking.com, among others.
Until 2005, we did not have a lot of data to create these algorithms or to tell them if they are working well..
When we have an imbalance, accuracy is not the right measure.
Wikimedia Research, in partnership with Google and other external collaborators, is hosting a competition with the WIT dataset in Kaggle.
This is the first time the data-centre category tests have run on an Arm-based system.
Primer’s improvements can be attributed to two simple modifications — squaring ReLU activations and adding a depthwise convolution layer after each Q, K, and V projection in self-attention.
IC-GAN can be used with both labelled and unlabelled datasets.
For instance, Facebook AI Research (FAIR) has been championing self-supervised learning (SSL) for quite some time.
In the future, we plan to optimise these models further and apply them to new tasks, such as zero-shot learning and self-supervised learning.
GRAND chip can effectively decode any redundancy code up to 128 bits in length, with only about a microsecond of latency.
SOAFEE is a new open-standards-based architecture for software-defined vehicles.
As smartphones are set to touch one billion Indians in the next five years, we hope India will become a land of not only gamers, but also creators, building an ‘atmanirbhar’ metaverse.
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