This means that it can take user's input text and transform it into what it predicts the most useful result will be based on the patterns recognized from the parameter library.
MACHINE LEARNING
-
How Language Models Function as Probabilistic Text Predictors
By
–
When a user provides the text input, the system analyzes the language and uses a text predictor to create the most likely* output. *Does not necessarily mean the most factually accurate output, but rather the most "likely" output based on the data from the training library.
-
Understanding Parameters in AI Models Like GPT-3
By
–
GPT-3 has a lot of "parameters" for guessing the next words in a sequence. What's a parameter? It's a variable within the model whose value can be estimated from the given data. They are required by the model when making predictions. GPT-3 has about 175,000,000,000 of them.
-
How AI Models Learn to Recognize Textual Patterns
By
–
The algorithm (or "model") utilizes a set of data that enables it to recognize certain patterns in the text. This is accomplished by training the system on the vast body of internet text to spot patterns.
-
CICERO by Meta AI: Strategic Dialogue Generation System
By
–
#CICERObyMetaAI generates strategic, free-form dialogue by: Predicting the moves other players are likely to make Creating a plan based on those predictions Generating messages Filtering the final messages for clarity and value Read more on our blog
-
ACM Gordon Bell Prize Awarded for HPC COVID-19 Research
By
–
Congratulations to our Solutions Engineers, Claire Zhang and Cindy Catherine Orozco Bohorquez, who recently received their ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research awards! Read the paper here: https://
hubs.li/Q01s_n7N0 -
Old NLP Experts Underestimate Language Models’ Capabilities
By
–
Some old-time NLPers can be closed minded about the "range of tasks" that LMs can do. They are still thinking about LMs through BERT, etc. I rarely see this issue with new-joiners to NLP.
-
Hugging Face Datasets Library Appreciation and Documentation
By
–
This is a @huggingface Datasets appreciation tweet! https://
huggingface.co/docs/datasets/
index
… -
Join TMLS Toronto Conference on Machine Learning
By
–
Come join us at @TMLS_TO 's Toronto Conference next week. Register here –> https://
torontomachinelearning.com #computing #machinelearning #tenstorrent #toronto -
Groq VP speaks on AI in financial services at STAC summit
By
–
Come hear Amr El-Ashmawi, VP of Vertical Markets, speak about #AI in #financialservices at the London #STACsummit on 11/30. Visit our booth too and ask us about our latest benchmarking results with STAC ML. Read more here: http://
groq.link/stacpr
#artificialintelligence #ML