Tokyo police have arrested three teenage boys on suspicion of fraudulently subscribing to Rakuten Mobile's phone service via a self-made program using artificial intelligence. The Metropolitan Police Department's cybercrime unit believes that the boys obtained at least about 2,500 mobile phone subscriptions in about six months from December 2023 and sold them for a total of about 7.5 million in crypto assets. The arrests were made for allegedly obtaining 105 mobile phone subscriptions between May and August last year by logging into the Rakuten Mobile system with other people's IDs and passwords. The boys -- a 14-year-old third-year junior high school student in Tokyo, a 16-year-old first-year high school student in Gifu Prefecture and a 15-year-old third-year junior high school student in Shiga Prefecture -- have admitted to the allegations, according to police sources. One of the three was quoted as saying that he wanted to attract attention on social media by devising and carrying out a sophisticated criminal scheme.

Trends show that artificial intelligence (AI) will be a major topic in 2023, as data indicates a surge in interest. Since interest peaked and Microsoft invested billions into Chatgpt, demand for AI-focused cryptocurrency projects has risen dramatically. For example, the crypto project Fetch.ai has seen its native token FET rise 212% in the past 30 days, and another AI project, Singularitynet, has seen it's token AGIX increase 293% against the U.S. dollar. During the week of Jan. 22-28, 2023, the worldwide Google Trends score for the term "AI" was 94 out of 100. In the first week of Dec. 2022, the search term reached its highest Google Trends score of 100.

In a recent article published in CoinDesk, I outlined some of the key challenges of quant strategies for crypto assets. Creating predictive models and quant strategies for crypto assets is a fascinating challenges and one that present very novel difficulties compared to traditional capital markets. As we have been building more machine learning(ML)-based predictive models at IntoTheBlock, we have encountered several hurtles that fall outside traditional machine learning and quant methodologies. One of those challenges is what I referred to in the article as the "retraining dilemma". ML-based predictive models for financial assets such as cryptocurrencies are fundamentally based in supervised learning methods.

Blockchain, IoT, and AI are innovative technologies which will pave the way of digital transformation and will disrupt various industries. These three technologies will converge and will create new business models: Autonomous agents (i.e., sensors, cars, machines, and other IoT devices) will act as own profit centers 1) that have a digital twin leveraging IoT, 2) that autonomously send and receive money leveraging blockchain technology and 3) that autonomously make decisions as independent economic agents leveraging AI and data analytics. We argue that this convergence of technologies will drive the development of such autonomous business models and the digital transformation of companies.[1] Currently, the interconnection between these innovations is mainly neglected. However, these innovations can and should be applied jointly and will converge in the future.

ITB is an intelligence company that uses machine learning and statistical modeling to deliver actionable intelligence for crypto assets. Our machine learning algorithms combine hundreds of factors to extract unique insights about your crypto asset portfolio. ITB provides insights about crypto assets that everyone, not only sophisticated traders, can understand. ITB creates a holistic view of a crypto asset by analyzing hundreds of on-chain and off-chain factors. ITB regularly produces new insights and indicators that reveal new intelligence about crypto markets. Indicators are divided into four main categories to provide users with a holistic view of a crypto asset's behavior Provide a view of crypto asset's "capital stack" according to ownership concentration and time held.

Artificial Intelligence or simply AI has been at the forefront of the latest advancements made by mankind. AI is indeed a revolutionary breakthrough of computer science, set to become a core component of all modern software over the coming decades. In general terms, AI refers to computational tools that are able to substitute for human intelligence in the performance of certain tasks. This technology is currently advancing at a breakneck pace, much like the exponential growth experienced by database technology in the late twentieth century. Databases have grown to become the core infrastructure that drives enterprise-level software.

In Act II, Scene II of the famous play Richelieu; Or the Conspiracy, British playwright Edward Bulwer-Lytton coined a phrase that has transcended generations: "The pen is mightier than the sword."

At the moment, most analytic platforms are using lazy analyses that are fundamentally misleading There are three main techniques for social/news media analysis: sentiment, topic and tone analysis No single method is enough by itself 38.

ITB is an intelligence company that uses machine learning and statistical modeling to deliver actionable intelligence for crypto assets. Our machine learning algorithms combine hundreds of factors to extract unique insights about your crypto asset portfolio. ITB provides insights about crypto assets that everyone, not only sophisticated traders, can understand. ITB creates a holistic view of a crypto asset by analyzing hundreds of on-chain and off-chain factors. ITB regularly produces new insights and indicators that reveal new intelligence about crypto markets.

Nasdaq might be on the cusp of giving institutional investors an analytical edge on trading hundreds of crypto assets. According to a person familiar with the company's plans, the U.S. stock exchange is preparing to add tools for predicting the price movements of crypto assets to its Analytics Hub. The hub, launched last year, draws on machine learning and natural language processing (NLP) capabilities to parse through social media and other alternative data sources to give investors a better way to assess market movement. To date, the Analytics Hub has focused on traditional assets, but the addition of crypto seems to be another signal of Wall Street's growing interest in the nascent sector. Bill Dague, Nasdaq's head of alternative data, told CoinDesk that "given the abundance of interest, we are exploring cryptocurrency related datasets." "Whether or not we launch a crypto-related product remains to be seen."