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Synerise S.A.

12.10.2021 23:16

Pracodawca

Synerise among the winners of Twitter RecSys AI Challenge 2021.

Polish scientists and engineers have once again proved that consistent investment in their own IP in the field of artificial intelligence is gaining global recognition. This time, just behind the specialists from NIVIDIA - a company currently valued at 500 billion dollars - they were among the winners of the most prestigious competition in the world related to recommendation systems, organized by Twitter.


Recently the Polish company dominated the most prestigious and demanding events in the world of AI, gaining awards in competitions such as SIGIR Rakuten Data Challenge 2020, WSDM Booking.com AI Challenge 2020, KDD Cup 2021 and Twitter RecSys Challenge 2021.

"Having won once in a global competition which involves outstanding specialists and the best AI companies in the world, it may come as a surprise when it becomes a regular trend, appreciated by the global community. This accomplishment means that the Synerise team can now take on the greatest in the world, building its own, independent technologies, proven on a mass scale. The effects of our work are not only appreciated in scientific competitions, but are also components of our platform, which already supports over 150 billion purchasing transactions yearly. In AI and Big Data, it is difficult to create an MVP. Either you have the capacity to create algorithms based on real-time traffic or you do not - the pragmatism of AI solutions is a key issue - hence our investments in our own database systems. Many companies in Poland and our part of Europe build solutions based on Western technologies, and imitate them. We wanted to build something of our own from the very beginning " - Jarosław Królewski, CEO of Synerise.  

Twitter RecSys AI Challenge 2021 is a competition organized by international research teams and Twitter specialists. The challenge is focused on advanced tasks in the field of recommendation systems and artificial intelligence. It attracts outstanding specialists from around the world.

The task set as part of the competition during RecSys2021, organized by the ACM (Association for Computing Machinery), was to predict the user's reaction to a given tweet, based on the content and metadata of the tweet and a graph of historical user interactions. The probability of each of 4 possible interactions had to be predicted — like, retweet, comment and retweet with a comment.

“An additional challenge of the task was the limitations imposed on the model evaluation phase. The models had only 1 CPU core with a time limit of 24 hours for making predictions. GPU accelerators were not available in the test environment. The rules set by Twitter were aimed at eliminating solutions that require significant computing power, often too expensive for production applications." — Jacek Dąbrowski, Chief AI Officer w Synerise.

The dataset contained 1 billion tweets selected by Twitter in a manner that assumed inclusiveness and fairness. It included tweets in dozens of languages (including Japanese, Thai and Tagalog) and a diverse selection of users, from very popular authors to completely new users.

The month of June was exceptionally successful for Synerise. Together with Baidu and DeepMind, Polish scientists and engineers from Synerise were among the winners of the KDD Cup 2021. The competition, running for 24 years already, is considered by the technology industry to be one of the most prestigious AI and machine learning events in the world and is often called the World Championships in the field of artificial intelligence. Synerise defeated teams from around the world, including specialists from Intel (manufacturer of computer processors), OPPO Research Topology Lab (manufacturer of OnePlus iOppo phones) and Huazhong University of Science and Technology.

Synerise.com is a Polish technology company that produces a Big Data and AI platform that allows users to process data in real time from various sources based on proprietary database systems, proprietary artificial intelligence algorithms as well as methods of automated execution of business scenarios for segments such as retail, banking, telecommunications and e-commerce. Synerise's clients include: CCC, Carrefour, Żabka, Orange, mBank, SharafDG.
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Synerise S.A.

25.11.2020 15:01

Pracodawca

Synerise releases Cleora AI framework for ultra-fast embeddings in large graphs as open-source


Artificial Intelligence company Synerise, one of the fastest growing in CEE, known for their AI Growth Ecosystem is open sourcing Cleora AI project – a machine learning tool that enables faster and hyper-easy production of graph embeddings for big graphs. Synerise has been working on the project during last few years and has developed an easy-to-use framework that can be applied to any data sets without limitations.




Cleora is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. The framework embeds entities in n-dimensional spherical spaces utilizing extremely fast, stable and iterative random projections, which allows for unparalleled performance and scalability. The tool can embed extremely large graphs & hypergraphs on a single machine. 

Types of data which can be embedded include for example:

1. Heterogeneous directed and undirected graphs,

2. Heterogeneous undirected hypergraphs,

3. Text and other categorical array data,

4. Any combination of the above.


At Synerise we believe that sharing knowledge and showing innovation in the open-source Cleora framework will help many companies to develop amazing, faster solutions in the AI field. – Barbara Rychalska – AI Research Scientist at Synerise.


Key technical features of Cleora embeddings

The embeddings produced by Cleora are different from those produced by Node2vec, Word2vec, DeepWalk or other systems in this class by a number of key properties:

1. Efficiency - Cleora is two orders of magnitude faster than Node2Vec or DeepWalk,


2. Inductivity - as Cleora embeddings of an entity are defined only by interactions with other entities, vectors for new entities can be computed on-the-fly,


3. Updatability - refreshing a Cleora embedding for an entity is a very fast operation allowing for real-time updates without retraining,


4. Stability - all starting vectors for entities are deterministic, which means that Cleora embeddings on similar datasets will end up being similar. Methods like Word2vec, Node2vec or DeepWalk return different results with every run,


5. Cross-dataset compositionality - thanks to stability of Cleora embeddings, embeddings of the same entity on multiple datasets can be combined by averaging, yielding meaningful vectors,


6. Dim-wise independence - thanks to the process producing Cleora embeddings, every dimension is independent of others. This property allows for efficient and low-parameter method for combining multi-view embeddings with Conv1d layers,


7. Extreme parallelism and performance - Cleora is written in Rust utilizing thread-level parallelism for all calculations except input file loading. In practice this means that the embedding process is often faster than loading the input data.




The key usability features of Cleora embeddings from the end-user perspective can be summarized as:   

1. Heterogeneous relational tables can be embedded without any artificial data pre-processing,

2. Mixed interaction and text data sets can be embedded with ease,

3. The cold start problem for new entities is easily solved,

4. Real-time updates of the embeddings do not require separate solutions,

5. Multi-view embeddings work out-of-the-box,

6. Incremental embeddings are stable with no need for re-alignment, rotations or other methods,

7. Extremely large data sets are supported and can be embedded within seconds/minutes.




Key competitive advantages of Cleora:

1. More than 197x faster than DeepWalk,

2. ~4x-8x faster than Pytorch-BigGraph depends on use case

3. Star expansion, clique expansion, and no expansion support for hypergraphs,

4. Quality of results outperforming or competitive with other embedding frameworks like PyTorch-BigGraph, GOSH, DeepWalk, LINE,

5. Can embed extremely large graphs & hypergraphs on a single machine.

Synerise it's positioning Cleora at the top together with tech giants. The quality of results outperform or are competitive with other embedding frameworks.  The scientific paper with the details will be published in 2 weeks.
The source code of the solution is already available on the 
Synerise GitHub account. 



A strong confirmation of the innovation of Cleora’s algorithms is that we use them as a part of the Synerise AI Growth Ecosystem. We’re leading the way not only in observing the reality happening around us, but in making a real contribution to science and in the process of creating it. - Jacek Dąbrowski - Chief Artificial Intelligence Officer at Synerise.



Cleora is used by Synerise for internal purposes, working together with Terrarium DB processing billions of datapoints in real-time and solving multi-modal challenges which involves graph data. Cleora algorithm is flexible and can be applied to different segments of the market, inter alia: retail, banking, and telco behavioral data at scale (billions of entities, trillions of interactions). Cleora is also used in input embeddings in EMDE (Efficient Manifold Density Estimation) that was also created by the Synerise Team.
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