Clearview AI has been fined £7.55 million ($9.5 million) by the UK's privacy watchdog for illegally scraping the facial images of UK residents from social media and the web. It was also ordered to stop obtaining the data of UK residents and to delete any it has already collected. "The company not only enables identification of those people, but effectively monitors their behavior and offers it as a commercial service. That is unacceptable," said UK information commissioner John Edwards in a statement. The UK's Information Commissioner's Office (ICO) opened a joint investigation with Australia into Clearview AI back in 2020, and issued a preliminary fine of £17 million ($21.4 million) against the company late last year.

When starting out with Data Science, there is so much to learn it can become quite overwhelming. This guide will help aspiring data scientists and machine learning engineers gain better knowledge and experience. I will list different types of machine learning algorithms, which can be used with both Python and R. Linear Regression is the simplest Machine learning algorithm that branches off from Supervised Learning. It is primarily used to solve regression problems and make predictions on continuous dependent variables with the knowledge from independent variables. The goal of Linear Regression is to find the line of best fit, which can help predict the output for continuous dependent variables.

Artificial intelligence (AI) is having its moment these days. No wonder it starts being used for business purposes. The companies like Google, Microsoft, and Salesforce are integrating Artificial Intelligence solutions as intelligence...

Does the breakthrough to general AI need more data and computing power above all else? Yann LeCun, Chief AI Scientist at Meta, comments on the recent debate about scaling sparked by Deepmind's Gato. The recent successes of large AI models such as OpenAI's DALL-E 2, Google's PaLM and Deepmind's Flamingo have sparked a debate about their significance for progress towards general AI. Deepmind's Gato has recently given a particular boost to the debate, which has been conducted publicly, especially on Twitter. Gato is a Transformer model trained with numerous data modalities, including images, text, proprioception or joint moments.

Abstract: Matrix factorization, one of the most popular methods in machine learning, has recently benefited from introducing non-linearity in prediction tasks using tropical semiring. The non-linearity enables a better fit to extreme values and distributions, thus discovering high-variance patterns that differ from those found by standard linear algebra. However, the optimization process of various tropical matrix factorization methods is slow. In our work, we propose a new method FastSTMF based on Sparse Tropical Matrix Factorization (STMF), which introduces a novel strategy for updating factor matrices that results in efficient computational performance. We evaluated the efficiency of FastSTMF on synthetic and real gene expression data from the TCGA database, and the results show that FastSTMF outperforms STMF in both accuracy and running time.

In the span of a few years, artificial intelligence (AI) has evolved from an emerging technology to taking center stage in companies of all sizes. This has been a consistent trend across industries, and adoption will continue to accelerate. According to a recent study by IDC, "60% of Forbes' Global 2000 companies will expand the use of artificial intelligence across all business-critical horizontal functions like marketing, legal, HR, procurement, and supply chain logistics by 2024."* AI is at the heart of SAP's strategy to help customers become intelligent, sustainable enterprises. Bringing transformative intelligence to every aspect of their business through ready-to-use AI capabilities in SAP applications for all business processes, such as lead-to-cash, design-to-operate, recruit-to-retire, and source-to-pay.

Developments in the field of artificial intelligence (AI) are moving quickly. The EU is working hard to establish rules around AI and to determine which systems are welcome and which are not. But how does the EU do this when the biggest players, the US and China, often have different ethical views? Political economist Daniel Mügge and his team will conduct research into how the EU conducts its'AI diplomacy' and will sketch potential future scenarios. "Our research is essentially about regulation around AI", says political economist Daniel Mügge.

You could soon see self-driving buses and delivery vans on UK roads as the government launches a £40m ($50m) competition to bring this technology to the market. The funding to kick-start commercial self-driving services, such as delivery vehicles and passenger shuttles, will help bring together companies and investors so that sustainable business models to be rolled out nationally and exported globally. The Commercialising Connected and Automated Mobility competition will provide grants to help roll out commercial use self-driving vehicles across the UK from 2025. Types of self-driving vehicles that could be deployed include delivery vans, passenger buses, shuttles and pods, as well as vehicles that move people and luggage at airports and containers at shipping ports. The competition aims to unlock a new industry that could be worth £42bn to the UK economy by 2035, potentially creating 38,000 new skilled jobs.

Social media has brought about a revolutionary change in the way of life and Predis.ai Predis.ai is a cloud-based AI-SAAS platform where users can get multiple Social Media Content options in just a few clicks. The users can also customize the platform to ensure their social media posts are in-sync with their brand language. The process is simple and starts with entering a one-line description of the product, business, or campaign and asking the AI to generate multiple post ideas. The users need not take any step further -- let the AI work for them as it will execute the post ideas and make Image creatives, captions, and hashtag options immaculately suggested to suit their brand.

This tutorial explains how to preprocess data using the Pandas library. Preprocessing is the process of doing a pre-analysis of data, in order to transform them into a standard and normalised format. In this tutorial we deal only with normalisation. In my previous tutorials I dealt with missing values and data formatting. Data Normalisation involves adjusting values measured on different scales to a common scale.