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Sergey Savastiouk's Avatar
published in Blogs
Mar 15, 2023

Artificial Intelligence for Language Translation?

Researchers are using artificial intelligence in new, creative ways. Some use cases – predicting earthquakes, recognizing objects, and comparing medical scans, for example – offer tantalizing glimpses of a promising future. Language translation has long been considered a natural application for AI, but processes are ripe for improvement. Now, MIT researchers have announced an “unsupervised” language translation model whose early returns signal a future with “faster, more efficient computer-based translations of far more languages.”

Most widely-used translation programs (like Google’s) learn via models. These programs are trained to “look for patterns in millions of documents – such as legal and political documents, or news articles” that have been translated from one language to another by humans. Once they identify a new word in one language, they can find its match in a different language through pattern analysis.

This approach, however, is labor intensive and inefficient – partially due to its reliance on specific translations from one language to another to accurately translate words. New “monolingual” models have attempted to rectify these issues by translating “without direct translational information between the two,” but are slow and require significant computing power to work.

To combat these pain points, MIT researchers with the Computer Science and Artificial Intelligence Laboratory (CSAIL) developed a new technique. By employing a statistical metric commonly used for pixel alignment called the Gromov-Wasserstein distance – which “essentially measures distances between points in one computational space and matches them to similarly distanced points in another space” – in conjunction with a vectorized system called “word embeddings”, where “words of similar meanings [are] clustered closer together,” researchers were able to create a system that can deduce likely direct translations via the relative distances of words within each vector. 

Using relational distances negates the time-consuming, laborious process of creating perfect word alignments. Gromov-Wasserstein is “tailor-made” for this purpose, said CSAIL Ph.D. student David Alvarez-Melis, who was the first author of the paper presenting the findings. “If there are points, or words, that are close together in one space, Gromov-Wasserstein is automatically going to try to find the corresponding cluster of points in the other space,” explained Alvarez-Melis.

Researchers are discovering innovative ways to utilize artificial intelligence. Applications such as earthquake prediction, object recognition, and medical scan comparisons show the potential for a promising future. While AI has long been employed for language translation, improvements are still necessary. MIT researchers have introduced an "unsupervised" language translation model that has demonstrated promising results, paving the way for faster and more efficient translations of a wider range of languages.

Commonly used translation programs, such as Google's, rely on models that learn by analyzing millions of translated documents, such as legal and political papers, and news articles. These models detect patterns to locate corresponding words in different languages when encountering a new word in one language.

While traditional approaches to translation rely on specific translations from one language to another, they can be labor-intensive and inefficient. Although new "monolingual" models attempt to solve this problem by translating "without direct translational information between the two," these models are often slow and require significant computing power.

To address these challenges, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) developed a new technique. They combined the Gromov-Wasserstein distance, a statistical metric commonly used for pixel alignment, with a vectorized system called "word embeddings." This system clusters words with similar meanings closer together, allowing researchers to deduce likely direct translations based on the relative distances of words within each vector.

Using relational distances eliminates the need for the time-consuming and laborious process of creating perfect word alignments. According to CSAIL Ph.D. student David Alvarez-Melis, the Gromov-Wasserstein distance is "tailor-made" for this purpose. He explains that if there are points or words that are close together in one space, the Gromov-Wasserstein distance will automatically try to find the corresponding cluster of points in the other space. For example, despite differences between languages, the model could identify a cluster of 12 vectors for the months of the year in one embedding and a similar cluster in the other embedding, allowing for simultaneous alignment of an entire vector space.

The result is a system with accuracy comparable to existing monolingual models but with greater speed and significantly less operating power. This is a significant step towards the goal of achieving truly unsupervised word alignment and demonstrates the power of AI being fine-tuned and deployed in new, creative, and useful ways.

If You’re Wondering When A.I. Will Start Making Market Predictions…

Did you know that Artificial Intelligence (A.I.) is already being used to make market predictions? Hedge funds and large institutional investors have been using A.I. to analyze vast amounts of data for investment opportunities and to identify patterns and trends in charts. The A.I. can scan thousands of securities and cryptocurrencies and generate trade ideas based on what it finds. However, retail investors have been at a disadvantage until now.

Tickeron has launched a new investment platform that provides retail investors with access to sophisticated A.I. for a variety of functions,

  •  including finding stock patterns and trends,
  •  testing portfolio diversification, 
  • back-testing trading results based on different stock patterns,
  •  and making predictions about future price movements with an "A.I. Rank" and level of confidence in the trade.

With Tickeron's platform, retail investors can level the playing field and take advantage of A.I. technology to make better investment decisions.

And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.

Tickeron’s Approach to Fintech: Artificial Intelligence for Retail Investors

Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.

Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:

Finding stock patterns in the market
Finding trends in the stock market
Testing portfolios to see if they are well-diversified
Back-testing statistics to see how different stock patterns generated trading results
Making Predictions for price movements in the future, with “A.I. Rank” and level of confidence in the trade.
And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.

Sergey Savastiouk's Avatar
published in Blogs
Mar 14, 2023
How to Start Trading Penny Stocks

How to Start Trading Penny Stocks

Penny stocks have long been marginalized within the professional investment community, oftentimes being painted with a broad brush of simply being “too risky.” Leonardo DiCaprio’s depiction of the penny stock peddling conman, Jordan Belfort, in the Wolf of Wall Street certainly didn’t help.Here are four reasons to start trading them now. Reason #1: Let’s State the Obvious -- Penny Stocks are Cheap A single share of Apple Inc. costs over $350.
Dmitry Perepelkin's Avatar
published in Blogs
Mar 14, 2023
5 Habits that Lead to Successful Investing

5 Habits that Lead to Successful Investing

To consistently make money in this industry, you need emotional fortitude, an analytical mind, and a willingness to self-reflect. Despite trading and investing being two different activities, these principles can be applied to both.Conversely, investors with good habits often become great traders.  Rather than full sentences for titles, we’ve labeled each of our top-five investing habits using a single word principle.
Allana's Avatar
published in Blogs
Mar 23, 2023
What’s the Difference Between Data Analytics and Machine Learning?

What’s the Difference Between Data Analytics and Machine Learning?

Artificial intelligence (AI) technology is developing rapidly.Data mining can deliver raw numbers, but it does not necessarily provide actionable insights. Structure is necessary to taking abstract information and extracting commonalities, like averages, ratios, and percentages.
Sergey Savastiouk's Avatar
published in Blogs
Mar 13, 2023
4 Tips for Fast, Effective Stock Analysis

4 Tips for Fast, Effective Stock Analysis

With just a few clicks, an investor can search for individual stocks, categories of stocks, sectors, or investment themes, and then he or she can conduct a full range of technical and fundamental analysis within seconds.All powered by Artificial Intelligence.  Below, we give you 5 tips for fast, effective stock analysis using Tickeron’s Screener.
Sergey Savastiouk's Avatar
published in Blogs
Mar 20, 2023
5 Golden Principles in Investing

5 Golden Principles in Investing

You have enough faith in that stock, based on research, that the return will equal or exceed the investment.  Do unto others.The principles outlined here will ensure that happens.  Principle #1: Diversification Investors can’t be one-dimensional when constructing a portfolio.
John Jacques's Avatar
published in Blogs
Mar 24, 2023
If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

Some of the world’s biggest financial institutions have devoted multi-million dollar budgets to developing algorithms that can find patterns in the market, identify trends, and perform automated trading designed to take advantage of even the smallest price movements. The AI revolution is so big that as it stands today, the world’s five biggest hedge funds all use systems-based approaches to trade financial markets.Indeed, quantitative trading hedge funds now manage $918 billion (according to HFR), which amounts to 30% of the $3 trillion hedge fund industry – a percentage continues to grow with each year that passes.
Sergey Savastiouk's Avatar
published in Blogs
Mar 15, 2023
The five most important Lessons Learned After 10,000 hours of Trading

The five most important Lessons Learned After 10,000 hours of Trading

Ten thousand hours of active trading, broken down into forty-hour weeks, amounts to almost five years. Having surpassed that milestone myself, I now understand why it's significant for any trader's journey. The early years taught me valuable lessons that have shaped my approach to trading. It's a misconception that great traders are born with innate talent. The truth is that it takes years of...
Edward Flores's Avatar
published in Blogs
Mar 12, 2023
What's the Difference Between Tokens and Altcoins?

What's the Difference Between Tokens and Altcoins?

Between their inherently technical nature, multiple varieties and sub-varieties, and endless terminology, cryptocurrency (defined here as digital or virtual currencies that are encrypted using cryptography, powered by the immutable digital ledger known as the blockchain) represents a whole, complex world.All altcoins possess their own blockchain, independent from their source code, that records all transactions of their native coins. Many altcoins are variants, or forks, of Bitcoin that leverage that cryptocurrency’s open-source protocol as the basis.
Edward Flores's Avatar
published in Blogs
Mar 26, 2023
Why it Pays to Invest in Dividend Stocks Over the Long Term

Why it Pays to Invest in Dividend Stocks Over the Long Term

Where smaller, more volatile companies can placate shareholders with higher returns, larger companies often use dividend payouts to entice new investors and hold their existing ones. These low-risk options may not work for every investment approach, but dividend-producing stocks can offer great benefits under the right circumstances – especially for portfolios built for the long-term.Beyond the ability to rely on these semi-regular payouts as an income stream – a strategy favored by retirees – dividends are an excellent vehicle for compounding earnings through reinvestment.
Edward Flores's Avatar
published in Blogs
Apr 02, 2023
How Artificial Intelligence Can Improve Fintech

How Artificial Intelligence Can Improve Fintech

Artificial intelligence (AI) and fintech have an inherent compatibility that has become clearer as each sector has matured, with recent growth and successes on their own accord bringing new ideas about how they can work together.AI can analyze information at far greater quantities (and far more quickly) than any human, making it a natural fit to help fintech firms streamline and automate processes that benefit customers and businesses alike. Fintech has brought a revolution of convenience to the finance world.