Alla Petriaieva's Avatar
Alla Petriaieva
published in Blogs
Mar 03, 2021
A.I. Increasingly Adept at Creating Images and Video

A.I. Increasingly Adept at Creating Images and Video

AI isn’t just for crunching data anymore. Machine learning has made great strides in analyzing diverse information, including images, but has struggled to generate realistic images on its own. Now recent strides have opened that new frontier, introducing a whole new level of accuracy, realism, to the mix – as well as potential problems.

One of the most exciting developments is an algorithm from members of Google’s DeepMind AI team. That algorithm, called BigGAN (Generative Adversarial Network), is not dissimilar from other GANs used in machine learning. Like most GANs, it leverages two models – a generative network that creates random images within masses of real images, and a discriminative network that tries to locate them. GANs are powerful, but typically limited, neural nets that require larger numbers of images in one category at a time – faces, trees, cats – in order to be effective. But backed by the computational resources of one of the world’s biggest companies, BigGAN could learn from a giant database of 14 million images in various categories at one time. The result was images that displayed an unprecedented level of realism in unparalleled variety.

AI’s newfound creativity doesn’t just extend to still images. UC Berkeley computer science researchers announced in August that they had developed a series of algorithms capable of taking video of dance moves and transposing them from one person to another – a process similar to the CGI techniques used by Hollywood to create computer-generated characters like Gollum from actual movements. Wired describes the software in action: Using 20 minutes of video, “One part of the software extracts the body positions from both clips; another learns how to create a realistic image of the subject for any given body position. It can then generate video of the subject performing more or less any set of movements.”

The implications are both exciting – AI-generated art! New, powerful creative tools!  – and concerning. Software called Deepfakes, which originated via an anonymous programmer on Reddit in 2017, uses GANs to swap faces in videos. It has been used in everything from art to porn; its versatility has prompted fears that it (or similar software) could be used for more nefarious purposes.

Those fears are slowly being realized. The Guardian reported on a video “…created by a Belgian political party, Socialistische Partij Anders, or sp.a, and posted on sp.a’s Twitter and Facebook,” that depicted Donald Trump advising Belgians to withdraw from the Paris climate agreement. It drew intense negative reaction, leading sp.a to clarify that it was not, in fact, a real video. In a political climate of election interference by foreign powers, deep distrust between parties, and the term ‘fake news’ being bandied about with regularity, there is justifiable concern that algorithm-derived videos could cause real problems.

Tim Hwang, director of the Harvard-MIT Ethics and Governance of Artificial Intelligence Initiative, thinks that day is not here quite yet. He argues that amateurs are better spent using simpler means, telling The Guardian, “If you are a propagandist, you want to spread your work as far as possible with the least amount of effort,” he said. “Right now, a crude Photoshop job could be just as effective as something created with machine learning.” But that time may be coming. “…In the past, if you wanted to make a video of the president saying something he didn’t say, you needed a team of experts,” said Hwang. “Machine learning will not only automate this process, it will also probably make better forgeries.”

AI is becoming steadily more powerful, easier to use, and more effective. The breakneck pace of innovation is exciting, but with that revolution comes big questions that will need to be answered. It’s not a question of if we will see AI-created images and video on a wide scale – it’s a question of when.

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Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Mar 07, 2021
4 Tricks Hedge Funds Use to Get Ahead

4 Tricks Hedge Funds Use to Get Ahead

If the stock market were Major League Baseball, hedge funds and institutional investors would be the pros on championship teams while everyday self-directed investors (SDIs) are the benchwarmers in the minors.It’s how they get ahead, and it’s why 90% of SDIs lose money trying to play (invest and trade) in the major leagues. The 4 tricks we discuss below are rooted in one common theme: they all use Artificial Intelligence and algorithms to generate data and ideas.
John Jacques's Avatar
John Jacques
published in Blogs
Mar 22, 2018
A.I. Stock Market Predictions: Head & Shoulders

A.I. Stock Market Predictions: Head & Shoulders

Statistics for the Head-and-Shoulders Bottom Pattern The days where only hedge funds used algorithms to trade stocks are officially over. Now retail investors can use Artificial Intelligence (A.I.  Here’s an example of the algorithm in action: Late last year, Tickeron’s A.I.
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Jul 10, 2020
3 Stocks to Buy if Coronavirus Second Wave Hits

3 Stocks to Buy if Coronavirus Second Wave Hits

By analyzing market trends from the first wave, you can predict behavior for the second. Technology stocks have performed at historic levels this year, but the market is severely overbought.To compensate for that, look at performance during Q1 and Q2, the height of global Covid shutdowns.
Edward Flores's Avatar
Edward Flores
published in Blogs
Feb 06, 2021
How to Become the Millionaire Next Door

How to Become the Millionaire Next Door

The Golden Gate Bridge is always a fixture of these walks too, one of man's most beautiful creations.  As we were walking, at one point she turned to me and said, "Man, I'll never have a million dollars."" My girlfriend is 27 years old and works as a graphic designer, making about $75,000 a year.
Alla Petriaieva's Avatar
Alla Petriaieva
published in Blogs
Feb 23, 2021
Is Ethereum’s Bomb about to Explode?

Is Ethereum’s Bomb about to Explode?

Ethereum’s software is set for an update in October.Until it is finished, participants in the Ethereum blockchain must determine how to delay the difficulty bomb – code that necessitates a steadily increasing amount of computer power to mine blocks and unlock rewards – that is already in place.
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Aug 07, 2018
When Is the Next Recession Coming?

When Is the Next Recession Coming?

However, we also know that economists predicted 22 recessions out of 11 that took place since 1945. Are there real recession signs we should watch for?Indeed, the answer is yes, and here are a few very important ones: The first one is almost obvious and known to everyone – it is the Fed.
Abhoy Sarkar's Avatar
Abhoy Sarkar
published in Blogs
May 22, 2020
Central banks have been buying $2.4 billion in assets every hour for the past two months

Central banks have been buying $2.4 billion in assets every hour for the past two months

Some $17.8 billion has been poured into  bond markets over the past week, the biggest move in more than three months.Around $3.5 billion has been invested into gold, the second largest on record. 
Rick Pendergraft's Avatar
Rick Pendergraft
published in Blogs
Feb 07, 2021
Mid-January Short Interest Report Shows 8 Stocks with Good Fundamentals and High Short Interest
Sergey Savastiouk's Avatar
Sergey Savastiouk
published in Blogs
Mar 10, 2021
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.
Abhoy Sarkar's Avatar
Abhoy Sarkar
published in Blogs
May 08, 2020
US unemployment rate jumps to 14.7%, the highest in series history

US unemployment rate jumps to 14.7%, the highest in series history

The U.S. economy’s employment fell by -20.5 million in April. The coronavirus crisis led to unemployment rate soaring to 14.7% in the U.S, the highest rate in the Bureau of Labor Statistics-tracked series history that goes back to 1948. However, the figures were better compared to several economists'/analysts' forecasts of 22 million job losses and 16% unemployment rate.  Another unemployment measure that includes those who have stopped looking for work as well as those holding part-time jobs for economic reasons also touched an all-time high of 22.8%.