Join our Paper Talks
Live meeting with experts: chance to discuss, network, share knowledge and experience
Follow the newest achievements in the ML world and stay up to date with state-of-the art developments
Regular meetings that anyone interested can participate in and discuss a
particular scientific paper
particular scientific paper
Stay up-to-date with upcoming meeting!
Last Paper:
The Forward-Forward Algorithm: Some Preliminary Investigations
The Forward-Forward Algorithm: Some Preliminary Investigations
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What are Paper Talks?
Paper Talks is our internal GetInData initiative created within the Advanced Analytics team. It was born from the need to follow the newest achievements in the machine learning world and stay up to date with state-of-the art developments. Our field of interest is around different hot topics in data science, especially machine learning and deep learning.
- For whom?Everyone interested in data science and machine learning is welcome to join the discussion, however, we used to be pretty curious about the details and did many deep dives, so the atmosphere is definitely more technical and academic than business oriented. If you are a data scientist or a machine learning engineer and you work either in industry or academia, surely you will be able not only to get something interesting from it for you, but also to contribute to the discussion by sharing your ideas and experience.
- FormulaOne-hour zoom meeting that will be recorded (but recordings won't be public). We encourage you to turn on the camera!
- PaperEveryone can submit candidate papers for next paper talks and before each meeting we vote for the one that we want to discuss next. The person who submitted a winning paper starts and moderates the meeting, but it's never a one-man-show; it's a free discussion where everyone is encouraged to share thoughts!
Previous Paper Talk
On the previous meeting we discussed a very interesting article on exciting new findings related to the recent development in the natural language processing field. The authors described an unpredictable phenomenon that we refer to as the emergent abilities of large language models. Such emergent abilities were defined as abilities that occur in models above a certain size and do not occur in small models.
Feel free to watch a video record from part of the meeting, and if you would like to read the paper with our comment, check it here:
On the previous meeting we discussed a very interesting article on exciting new findings related to the recent development in the natural language processing field. The authors described an unpredictable phenomenon that we refer to as the emergent abilities of large language models. Such emergent abilities were defined as abilities that occur in models above a certain size and do not occur in small models.
Feel free to watch a video record from part of the meeting, and if you would like to read the paper with our comment, check it here:
- How can I contribute to the meeting?We want to encourage everyone to discuss at the meeting and add their thoughts to the paper even before the event. If you would like to do this, just open the (link) with paper, mark the selected part of the text add comments.
Previous Paper Talks
So far we managed to organize nearly 20 such meetings internally and since the formula seems to be working nicely, we want to share this initiative with a broader machine learning community.
We have discussed several topics, mostly in the area of advanced machine learning and deep learning. Usually, the papers were about:
We have discussed several topics, mostly in the area of advanced machine learning and deep learning. Usually, the papers were about:
Novel approaches to certain business use cases (e.g. state of the art designs in recommender systems, image synthesis with diffusion models etc.)
Cross-cutting comparative studies of different methods (e.g. modern applications of graph neural networks, evaluation of different methods in time-series anomaly detection etc.)
Empirical studies of important ML concepts (deep double descent, comparison of deep learning vs. tree-based algorithms on tabular data etc.)
We help data-oriented organizations to succeed using open-source and cloud technologies such as Flink, Kafka, Spark, Hadoop, Google Cloud Platfrom by providing outsourcing, consulting and training services.
We've been already working for tens of companies ranging from fast-growing European startups to global corporations in pharmacy, FMCG, banking and media sectors. We trully focus to help our customers achieve true ROI from their data processing.
We've been already working for tens of companies ranging from fast-growing European startups to global corporations in pharmacy, FMCG, banking and media sectors. We trully focus to help our customers achieve true ROI from their data processing.
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