Skip to main content

Artificial intelligence is expected to get smarter much faster thanks to Gamalon

gamalon machine learning bps technology ai google draw feat
Google
Artificial intelligence is getting a boost in its ability to learn. On Tuesday, a company called Gamalon revealed a new technology for machine learning called Bayesian Program Synthesis (BPS). This technology supposedly accelerates the machine learning process by more than 100 times and is available now in two commercialized alpha applications: Gamalon Structure and Gamalon Match.

In a demonstration, the company revealed how BPS learns compared to Google DeepMind’s machine learning. In Google’s “Quick, Draw!” app, the AI can recognize a single object drawn by the user, such as a floor lamp, by comparing it to the same object drawn by other users. But if the user draws a chair next to the floor lamp, the AI gets confused and shows that the user didn’t follow its instructions to draw a floor lamp, but rendered a house or church instead.

Recommended Videos

For BPS, the AI was trained by first defining what makes a line, then what makes specific shapes. After that, the AI was taught how an armchair is built by using rectangles and lines, first starting with the seat and armrests, followed by the armchair’s backrest in a separate element. This method was also used to teach the AI about floor lamps by defining the lamp post, the lamp base, and the lamp shade.

Thus, in a nutshell, Google’s AI got confused because it couldn’t recognize two separate objects. However, the BPS system not only recognizes two separate objects, but it will see and confirm those objects when other unrecognized elements are drawn into the same space. What the BPS system can’t do is recognize heavily altered objects, such as lamps with elements consisting of different sizes and locations. In other words, unless otherwise taught, BPS can’t recognize a table lamp or desk lamp.

“Going beyond this drawing application, we are starting to teach the system to read, first by building up letters, then words, and then sentences. Language is a much more complex setting, but like with drawing, we expect that the system will learn more and more complex concepts made out of simpler ones,” the company said.

Ultimately, the BPS method uses far less training examples than traditional deep machine learning, thus speeding up the overall learning process. As an example, the company said that in one test, DeepMind’s AI required 500 training examples while the BPS system only needed a handful of training examples to meet the same level of accuracy.

The two commercialized applications based on the new BPS learning system target the enterprise sector. Gamalon Structure will convert text paragraphs found in databases or documents into clean, structured data rows. The Gamalon Match application then deduplicates and links these data rows. Typically, these two tasks combined require large teams and years of work to generate the same results.

The two applications are available now as APIs within cloud platforms offered by Amazon, Microsoft, and Google.

Kevin Parrish
Former Digital Trends Contributor
Kevin started taking PCs apart in the 90s when Quake was on the way and his PC lacked the required components. Since then…
Read the eerily beautiful ‘synthetic scripture’ of an A.I. that thinks it’s God
ai religion bot gpt 2 art 4

Travis DeShazo is, to paraphrase Cake’s 2001 song “Comfort Eagle,” building a religion. He is building it bigger. He is increasing the parameters. And adding more data.

The results are fairly convincing, too, at least as far as synthetic scripture (his words) goes. “Not a god of the void or of chaos, but a god of wisdom,” reads one message, posted on the @gods_txt Twitter feed for GPT-2 Religion A.I. “This is the knowledge of divinity that I, the Supreme Being, impart to you. When a man learns this, he attains what the rest of mankind has not, and becomes a true god. Obedience to Me! Obey!”

Read more
This tech was science fiction 20 years ago. Now it’s reality
Hyundai Wearable Exoskeleton, assistive tech

Twenty years really isn’t all that long. A couple of decades ago, kids were reading Harry Potter books, Pixar movies were all the rage, and Microsoft’s Xbox and Sony’s PlayStation were battling it out for video game supremacy. That doesn’t sound all that different from 2021.

But technology has come a long way in that time. Not only is today’s tech far more powerful than it was 20 years ago, but a lot of the gadgets we thought of as science fiction have become part of our lives. Heck, in some cases, this technology has become so ubiquitous that we don’t even think about it as being cutting-edge tech.

Read more
Scientists are using A.I. to create artificial human genetic code
Profile of head on computer chip artificial intelligence.

Since at least 1950, when Alan Turing’s famous “Computing Machinery and Intelligence” paper was first published in the journal Mind, computer scientists interested in artificial intelligence have been fascinated by the notion of coding the mind. The mind, so the theory goes, is substrate independent, meaning that its processing ability does not, by necessity, have to be attached to the wetware of the brain. We could upload minds to computers or, conceivably, build entirely new ones wholly in the world of software.

This is all familiar stuff. While we have yet to build or re-create a mind in software, outside of the lowest-resolution abstractions that are modern neural networks, there are no shortage of computer scientists working on this effort right this moment.

Read more