Hey MLL we know that Day 29 & Day 30 Interview Preparation material is left to be uploaded. Apologise for delays but we are constantly putting our efforts on thinking how to provide enough value to your preparations with this last 2 notes. But now we are almost done with it. Notes will get uploaded by tonight. 💯
And for your acknowledgement something amazing is coming after the end of Interview Preparation Questions.
Uber AI Plug and Play Language Model (PPLM)
PPLM allows a user to flexibly plug in one or more simple attribute models representing the desired control objective into a large, unconditional language modeling (LM). The method has the key property that it uses the LM as is – no training or fine-tuning is required – which enables researchers to leverage best-in-class LMs even if they don't have the extensive hardware required to train them.
PPLM lets users combine small attribute models with an LM to steer its generation. Attribute models can be 100k times smaller than the LM and still be effective in steering it
PPLM algorithm entails three simple steps to generate a sample:
* given a partially generated sentence, compute log(p(x)) and log(p(a|x)) and the gradients of each with respect to the hidden representation of the underlying language model. These quantities are both available using an efficient forward and backward pass of both models;
* use the gradients to move the hidden representation of the language model a small step in the direction of increasing log(p(a|x)) and increasing log(p(x));
* sample the next word
more at paper: https://arxiv.org/abs/1912.02164
blogpost: https://eng.uber.com/pplm/
code: https://github.com/uber-research/PPLM
online demo: https://transformer.huggingface.co/model/pplm
#nlp #lm #languagemodeling #uber #pplm
PPLM allows a user to flexibly plug in one or more simple attribute models representing the desired control objective into a large, unconditional language modeling (LM). The method has the key property that it uses the LM as is – no training or fine-tuning is required – which enables researchers to leverage best-in-class LMs even if they don't have the extensive hardware required to train them.
PPLM lets users combine small attribute models with an LM to steer its generation. Attribute models can be 100k times smaller than the LM and still be effective in steering it
PPLM algorithm entails three simple steps to generate a sample:
* given a partially generated sentence, compute log(p(x)) and log(p(a|x)) and the gradients of each with respect to the hidden representation of the underlying language model. These quantities are both available using an efficient forward and backward pass of both models;
* use the gradients to move the hidden representation of the language model a small step in the direction of increasing log(p(a|x)) and increasing log(p(x));
* sample the next word
more at paper: https://arxiv.org/abs/1912.02164
blogpost: https://eng.uber.com/pplm/
code: https://github.com/uber-research/PPLM
online demo: https://transformer.huggingface.co/model/pplm
#nlp #lm #languagemodeling #uber #pplm
The 2019 AI Index report!
Stanford University Human-Centered Artificial Intelligence released an annual report about the state of #AI this year. 160 pages of text with various metrics and measurements. Good to read with a cup of coffee ;)
TL;DR by TheVerge in the picture but inside report more interesting!
site of the report: https://hai.stanford.edu/ai-index/2019
Stanford University Human-Centered Artificial Intelligence released an annual report about the state of #AI this year. 160 pages of text with various metrics and measurements. Good to read with a cup of coffee ;)
TL;DR by TheVerge in the picture but inside report more interesting!
site of the report: https://hai.stanford.edu/ai-index/2019
Stanford Institute for Human-Centered Artificial Intelligence
AI Index 2019
What is Data Science ? 100% off udemy coupons
#Data_Science
https://edutreasure.online/what-is-data-science-100-off-udemy-coupons/
#Data_Science
https://edutreasure.online/what-is-data-science-100-off-udemy-coupons/
MyWays.in, an IIT Delhi and Government of India incubated startup, is hiring full time employees and interns (6 months internships) in the field of Business Development, Machine Learning Engineer and Full Stack Development (MERN).
Location: Delhi
CTC: 10-20k per month
Apply here only for full time: https://forms.gle/fTaYdEga2XW9PMyTA
Location: Delhi
CTC: 10-20k per month
Apply here only for full time: https://forms.gle/fTaYdEga2XW9PMyTA
Anyone interested for internship in Ahemdabad? If yes then dm us on instagram.