👀Looking for something interesting? Welcome to open and free webinars from MIT professors:

1) Banach Space Representer Theorems for Neural Networks - Prof. Robert D. Nowak
https://www.csail.mit.edu/event/cbmm-special-seminar-banach-space-representer-theorems-neural-networks
June 8, 14:00 EST
https://mit.zoom.us/j/97306008379?pwd=OVR2MU1uNXcrcU5DZkRncmlnZndMZz09
Passcode: 289045

2) Next-generation recurrent network models for cognitive neuroscience - Guangyu Robert Yang
https://www.csail.mit.edu/event/cbmm-special-seminar-next-generation-recurrent-network-models-cognitive-neuroscience
June 15, 14:00 EST
https://mit.zoom.us/j/94734403753?pwd=YW5udzZJdndqVnc1NnkyQ0s3L0hVUT09
Passcode: 080128

🥁AI in retail: 7 examples
eBay - Pricing and stockpiling, optimizing the appearance of product cards to increase appeal and increase sales
Sephora uses a color matching recommendation system for color cosmetics (lipstick, eyeshadow and powder): the camera scans the skin color, analyzes the data and generates a unique color number and selects the product from the product line that suits this client best.
Tesco - inventory management: forecasting and replenishing with weather and regional characteristics, as well as data from CCTV cameras directed to store shelves. And routing ML-algorithms help buy faster in Tesco Online.
OTTO - Predicting future purchases based on the analysis of 3 billion historical transactions and 200 additional variables (weather, website searches, etc.). The accuracy of the forecast of which product will be sold within a month reaches 90%. This helps to optimize warehouse stocks and increase product turnover.
Simbe Robotics creates robots that detect violation of the plan for the placement of goods, their lack of goods and non-compliance with price tags using computer vision systems. She not only recognizes products, but also recommends how to fill them.
Vekia has developed a supply chain management solution for Leroy Merlen, Etam, Okaidi and Jacadi: control of goods in each store with daily assortment assessments. The system calculates the optimal stock level for each location several times a day and can automatically generate an order for the required items.
Diwo - determination of the factors of decrease in sales for individual products. The ML system also offers a set of recommended strategies for improving the situation, suggesting the ideal time to start promotions and other attributes of advertising campaigns.

🙌🏻Mathematics for the Data Scientist, Part 1: Benford's Law
Benford's (Newcomb-Benford) law of the first digit describes the probability of occurrence of a certain first significant digit in distributions of quantities taken from real life. This mathematical law is true for many distributions, it allows you to predict the frequency of occurrence of the second and third digits in the dataset.
For the first time this law was discovered by the American astronomer Simon Newcome in 1881, analyzing the degree of wear and tear of book pages. And in 1938, physicist Frank Benford made similar conclusions based on the results of the analysis of tables on the characteristics of rivers, chemical compounds and house numbers in the city directory. An analysis of numbers showed that one is the first significant digit with a probability of not 1/9, as it seems at first glance, but about 1/3.
Benford's Law applies to sets of numbers that can grow exponentially, i.e. the rate of growth of a value is proportional to its current value, for example, stock balances in warehouses, stock prices, population size, length of rivers, area of countries.A set of numbers satisfies Benford's law if the first digit d (𝑑∈1,…, 9) occurs in the equation. Using this distribution, you can predict which digit occurs most frequently in the dataset. The law usually does not apply for distributions with given minimum or maximum values, as well as those that cover only one or two orders of magnitude. Also Benford's law does not apply to texts. The sample size for the law of the first digit should be sufficient to apply statistical methods. In practice, the first digit law is applied in applications for detecting fraud in tax forms, election results, economic performance and accounting data.

💃🏼🕺🏼Smart clothes is a new fashion in the coming years: digital ML fabric from MIT researchers with memory, temperature sensors and a trained neural network
MIT has created the first digitally capable fiber that can detect, store, analyze, and measure physical activity after being sewn into a shirt. Digital fibers enhance the ability of tissues to detect hidden structures in the human body, which can be used to monitor physical performance, medical reports and early detection of diseases, as well as retain impressions. For example, memorize wedding music in the dress you were wearing that day.
Until now, electronic fibers have been analog, carrying a continuous electrical signal, not digital. This is the first implementation of a structure with the ability to digitally store and process data, allowing a new dimension of content to be added to textiles to program fabrics.
The new fiber was created by placing hundreds of square silicon digital microchips in a preform, which was then used to create a polymer fiber. By precisely controlling the flow of the polymer, the researchers were able to create a fiber with a continuous electrical connection between the chips for tens of meters.
The fiber itself is thin and flexible, it can be passed through a needle, sewn into fabric and washed at least 10 times without breaking, and it is also not felt at all. Thanks to the digital addressing method, it is possible to include the functionality of one element without affecting the rest of the elements. Digital fiber can also store a large amount of information in memory. The researchers were able to record, store and read information about the fiber, including a 767-kilobyte full-color short video file and a 0.48-megabyte music file. Files can be stored for two months without power.
The fiber includes a neural network of 1,650 connections in tissue memory, which can be trained on data in real time directly on a person, analyzing information about body temperature taking into account physical activity. Thanks to this, in the future, clothing will be able to detect and warn people in real time about changes in health indicators (respiratory and heart rate) and transmit data about muscle activation to athletes during training. Now the smart fabric is controlled by a small external device, and in the future it is planned to develop a new chip as a microcontroller connected to the fiber itself.
https://news.mit.edu/2021/programmable-fiber-0603

☀️Improve image quality using neural networks? No problem! ML-technology DeepHD from Yandex: GAN-networks make images better, removing interference and noise from them. https://yandex.ru/company/technologies/deephd/

👀How to create your own Deep Fake without the long training of neural networks? It's easy!
Try 4 free services:
- https://reface.app/
- https://avatarify.ai/
- https://www.wombo.ai/
- https://www.myheritage.com/deep-nostalgia?lang=RU
You need only upload a photo or make a selfie from your mobile phone to get a believable video of another person's face. For example, MyHeritage, a genealogical website, allows reanimate died people by generating mini-videos of them watching and smiling. However, remember that generating fakes to compromise someone can be considered libel and punishable by law!👆🏻

🥁ML-leader from Sber in IT World Awards 2021
The cloud platform ML Space from SberCloud (Sber) was recognized as the best Data Science and AI product in the world according to the organizers of the IT World Awards 2021, the Globee Awards. ML Space is a powerful MLOps data tool supporting all processes in the ML-model development cycle, including testing and deployment. The platform integrates all the necessary frameworks and libraries that allow you to speed up, optimize and simplify the processes of creating ML products.
https://globeeawards.com/it-world-awards/winners/

🤣Communication with photo and video bots: a study of how people reflect the emotions of virtual interlocutors, trusting their appearance and emotions. The conclusions of the scientists will surprise you: mirroring is not at all an indicator of a pleasant conversation, but an indicator of the difficulty in understanding an opponent.
https://techxplore.com/news/2021-06-features-virtual-agents-affect-humans.html

💥Mathematics for the Data Scientist, Part 2: Zipf's Law
This empirical pattern of natural language word frequency distribution is often used in quantitative linguistics and NLP problems. Zipf's law says: if all words in a large text are ordered in descending order of frequency of their use, then the frequency of the n-th word in this list will be inversely proportional to its ordinal number n (rank). For example, the second most commonly used word occurs about two times less often than the first, the third - three times less often than the first, etc.
The pattern was first discovered by French stenographer Jean-Baptiste Estoux in 1908. In practice, the law was applied to describe the distribution of city sizes by the German physicist Felix Auerbach in 1913. And the American linguist George Zipf actively popularized this pattern in 1949, proposing to use it to describe the distribution of economic forces and social status: the richest person has twice as much money as the next rich man, etc. An explanation of Zipf's law based on the correlation properties of additive Markov chains (with a step memory function) was given in 2005. Mathematically, Zipf's law is described by the Pareto distribution (the well-known 80 to 20 principle).
The different areas of application of the law (not only linguistics) are explained by the American bioinformatics specialist Wentian Li, who proved that a random sequence of characters also obeys this Zipf's law. Scientist argues that Zipf's law is a statistical phenomenon that has nothing to do with the semantics of a text, and the probability of a random occurrence of any word of length n in a chain of random characters decreases with increasing n in the same proportion as the rank of this word in the frequency list (ordinal scale). Therefore, the multiplication of the rank of a word by its frequency is a constant.

😜Welcome to office with a smile!
Canon's biometric access control systems passes into Chinese offices and other work areas only those employees who smile: a smile identification function is built into the face recognition module in video cameras at the entrance. This is expected to enhance corporate spirit and employee loyalty.)
https://www.theverge.com/2021/6/17/22538160/ai-camera-smile-recognition-office-workers-china-canon

👍🏻One word is enough: Facebook AI announced a new project, TextStyleBrush, capable of copying the style of handwritten or typed text on an image using only one word. This is useful for changing and replacing text in photos. Unlike previous AI systems capable of copying text from photographs, TextStyleBrush can work with all types of calligraphy and typography, interpreting various rotations and transformations of text, from curved characters to the natural deformation of paper from pressing a pen. It is important that Facebook understands the possibility of misuse of the TextStyleBrush for malicious acts such as text deepfakes. To prevent such attacks, the company will share research results with the Deepfake Detection Challenge dataset, contributing to the broad knowledge base of DL-fakes.
https://techxplore.com/news/2021-06-facebook-ai-word-mimic-text.html

💥The future of AI chips: a long history of collaboration and confrontation between AI giants to develop DS solutions. NVIDIA vs Google, the prospects for the development of deep neural networks and microcircuits, as well as money, cats and the Internet. https://www.wired.co.uk/article/nvidia-ai-chips

👆🏻10 the most interesting DS-conferences all over the world in July 2021
• 11.07 - MDA 2021: 16th International Conference on Mass Data Analysis of Images and Signals with Applications in Medicine, Biotech, and more. New York, NY, USA.
• 12.07 International Conference on Mobile Geomatics and Geodata Science (ICMGGS) - Ottawa, Canada https://waset.org/mobile-geomatics-and-geodata-science-conference-in-july-2021-in-ottawa
• 14.07 MLCon - The AI and ML Developer Virtual Conference, online https://cnvrg.io/mlcon/
• 18.07 - MLDM 2021: 17th International Conference on Machine Learning and Data Mining. New York, NY, USA http://www.mldm.de/
• 18.07 - International Conference on Machine Learning 2021. Online https://icml.cc/
• 20.07 - Chief Data & Analytics Officers (CDAO) Government Live, leading data-driven transformation across the government sector by Corinium. Online https://cdao-gov.coriniumintelligence.com
• 21.07 - Subsurface™ LIVE Summer 2021 - Free and Virtual https://www.dremio.com/subsurface/live/
• 22.07 - Business of Data Festival – Online https://www.boddigitalbroadcast.com/festival/home
• 22.07 - MarketsandMarkets Big Data Virtual Summit. Online https://events.marketsandmarkets.com/2nd-edition-marketsandmarkets-big-data-virtual-summit/
• 26.07 - The 2021 International Conference on Data Science (ICDATA'21). Las Vegas, NV, USA https://icdata.org/

👁Preparing for code review, speeding up development and testing with Copilot for Visual Studio from OpenAI
Write faster and better in Python, JavaScript, TypeScript, Ruby, Go, and a dozen other languages. Copilot runs on Codex, a new AI system from OpenAI, and understands more context than IDE helpers. Whether it's a docstring, a comment, a function name, or the code itself, Copilot uses context and synthesizes the instructions you need to help the developer create a quality product. https://copilot.github.com/

🏸Game theory as an engine for large-scale data analysis
A new look at principal components analysis as a competitive game, where each approximate eigenvector is controlled by the player, whose goal is to maximize his own utility function. As a multi-agent perspective, it has allowed the development of new ideas and algorithms with the efficient use of the latest computing resources, globally scaling datasets. Brief overview https://deepmind.com/blog/article/EigenGame and detailed article https://openreview.net/forum?id=NzTU59SYbNq

🥁NetHack Challenge at NeurIPS 2021 from Facebook: open-source project for Reinforcement Learning (RL) as a game
Many advances in RL have been achieved through simulation environments in games such as Dota 2, Minecraft, and StarCraft II. But this requires a lot of computation on thousands of GPUs at a time for just one experiment. To reduce the cost of RL modeling, Facebook in 2020 initiated the development of the open-source NetHack Learning Environment project. And in 2021, Facebook announced the NeurIPS 2021 competition as part of the NetHack Challenge in conjunction with AIcrowd, an AI crowdsourcing organization. The competition runs from early June to October 15, 2021, and the winners will be announced on NeurIPS in December.
The NetHack game has actually existed since the 1980s. It is visually straightforward and completely free to play, but more complicated than StarCraft II due to the very confusing interaction of players with their environment and related objects, users have to think outside the box or refer to the NetHack Wiki. And the main difficulty of NetHack is that after the death of a character, the game session of this player ends. Therefore, within this RL environment, researchers hope to find new ways to control agents so that in the future, AI can think creatively in difficult situations, helping people. Because NetHack runs on a terminal, players can quickly simulate gameplay by training billions of agents a day on just 2 GPUs. This is how the NetHack Challenge tests the latest AI techniques in a complex environment without the enormous power of a supercomputer. https://techxplore.com/news/2021-06-facebook-nethack-neurips.html

✍🏻Need a quick rewrite? Try NLPAug!
NLPAug is a Python library that allows you to increase the efficiency of neural networks in NLP tasks without changing their architecture and fine-tuning. With it, you can synthesize new text based on the available data, replacing some words with synonyms, incl. by the principle of cosine similarity in vector representations, similar to word2vec or GloVe. NLPAug also performs context-based word replacement using transformers in the form of BERT networks and makes double translation of text into another language and vice versa. https://github.com/makcedward/nlpaug

☀️ML for prediction of Solar Radiation
From a practical agronomic point of view, an accurate assessment of solar radiation is vital because it is a key factor in crop development. Most existing weather stations around the world have temperature and rain sensors, but only some of them measure solar radiation. Measuring solar radiation is usually very expensive due to complex sensors (pyranometers and radiometers) and a lack of reliable data. Therefore, a group of researchers from the University of Cordoba has developed ML-models to predict solar radiation in southern Spain and the United States.
The created ML-models are based not only on actual measurements, but are enriched with data on the geoclimatic conditions of the area (aridity, distance to the sea, altitude, etc.). To estimate daily solar radiation, the proposed neural network algorithms from current data only need information about the air temperature, which is relatively cheap due to inexpensive sensors and IoT technologies. Bayesian algorithms are used to optimize hyperparameters, and the models themselves can be adapted to any terrain, depending on its aridity.
https://techxplore.com/news/2021-07-machine-based-thermal-solar.html

🌦Why is it raining not as predicted and how Yandex Meteum 2.0 deals with it
The story about replacing MatrixNet with CatBoost and new datasets for training NN models. Now Meteum neural nets learn not only on data from professional weather stations, but also on information about terrain features and user messages. https://tekdeeps.com/yandex-has-launched-meteum-2-0-a-new-technology-for-weather-forecasting-based-on-machine-learning/

✈️AI will schedule flight crews for the US Air Force
The AI system from MIT helps US Air Force pilots plan the workload of personnel on cargo flights, based on many factors: airspace availability, pilot tolerances, work and rest requirements, etc. Combining optimization through integer programming with RL neural networks, the system generates flight schedules based on explicit and implicit constraints. https://news.mit.edu/2021/us-air-force-pilots-artificial-intelligence-assist-scheduling-aircrews-0708

🔥Video translation form Yandex
On July 16, 2021, Yandex showed the world's first prototype of machine video translation based on AI technologies of biometrics, speech recognition and speech synthesis. With its help, users of the desktop Yandex Browser can already watch videos in English with voice-over translation. The product will support other languages in the future. https://yandex.ru/company/services_news/2021/2021-07-16
Video:
https://disk.yandex.ru/d/7DYUm9QSfTPn5A
https://www.youtube.com/playlist?list=PLkMNi_iVG-shtwkqd918VUJ80NIOJ2pQf