P&L AI

Authors: Igor Arsenin and Arturas Vaitaitis Can Crypto Find a Purpose? A Blockchain Approach to Optimizing Neural Networks As training ever-larger transformer-based models encounters diminishing returns, a novel blockchain protocol could advance AI by emphasizing the optimization of neural network architectures, harnessing the decentralized computational power of blockchain technology. The innovative protocol would replace arbitrary decryption tasks in the proof-of-work concept with a focus on enhancing benchmark scores of AI models on standardized datasets, utilizing interfaces like the Open Neural Network Exchange (ONNX) protocol to define architectures. The economic potential of blockchain technology could draw a diverse range of players into the field, sparking a competitive drive for the development of more efficient and effective neural networks, potentially giving blockchain a purpose beyond digital currency while democratizing the field of AI. The remarkable progress in large l

China most incredible economic stratospheric economical rise is nothing short of economical miracle of 2021. A prevailing view among economists [2] is that much of China's rapid economic growth can be attributed to two main factors: large-scale capital investment by both large domestic savings and foreign investment and rapid productivity growth. The two factors happened concurrently and created mutually amplified effects, rapid productivity lead to more investments, which led to more productivity gains. Besides economical growth, both factors contributed to the largest social transformation resulting China lifting more than 100 million citizens from poverty and resulting in a mass movement of people from impoverished rural areas into metropolitan sections of the large cities.  This article expresses quite different point of view with different foregoing conclusions about why this incredible growth happened and what is going to follow. In my opinion, both contributing factors, were

Part of my covid project and part of my long obsession with prediction markets, I have created a web page that displays and allows to compare best and worst performing trading strategies. TL;DR: best stocks + best strategies -> the list of top and bottom performing trading algorithms.  Product Typically, trading newsletters and stock-scanners display only price return for top market gainers and losers. I have forever been interested in inspecting top and bottom performing trading strategies for a given set of securities and could not find any websites that do that. So, I decided to create a tool of my own. I wanted the tool that would help me to answer questions like if there is a better strategy than buy and hold, should I follow greed and fear indicator of the market or do the opposite. Top and bottom performing securities do not tell you if a stock is going to go up or down, but they do alert you to rapidly changing market conditions, such as change in the competitive landscape,

KX Meetup NLP presentation

Can news trending foreshadow market impact and returns? TL;DR: I developed a simple model of finding and measuring rate of propagation of financial memes in news. I also tested correlation between number of news trending up with a stock return momentum continuing, especially if it's a negative return. I called this model - Newsd.ai! Scenario Here is a practical example, during and in the immediate aftermath of sudden market moves, we need to distinguish between the following scenarios resulting from breaking news coming about the company or instrument: price move is instant and atomic, leaving no time to react price move becomes a trend, as story keeps developing Newsdai model breaks stories into 2 groups. Most of the stories are restatement of the event post-factum or trivial statement of facts that nonetheless leads to a singular "atomic" price move that creates a jump in return. This category leaves no time to form an actionable strategy or trade. If the event happen a

Please check out the previous  series on evolution  as introduction to this preface. Financial markets are best forecasting tools My fascination with the subject of evolution as a forecasting algorithm, see Great Question Part IV - Evolution as an algorithm ,  resulted in my own desire to create an algorithm that forecasts events in the setting of financial markets. Financial markets are best forecasting tools that we have developed so far, whether when the forecasting is done 1 year or 1 ms ahead. The best way to forecast and profit from knowing the future is to analyze reactions of financial market to the past events and draw conclusions from that. This is how an idea of the Newsdaq came from. I wanted to create an eco-system where the players who would make correct decisions would be rewarded without paying too much of a penalty, but have enough at stake to care for decisions they are making.  Newsdaq Newsdaq was a both a shared economy marketplace for amateur research