Some applications of technology are just ... strange. That being said, I think there's something beautiful about science being done "just to see if we can".
Not every experiment needs to be in pursuit of some grand truth or miracle cure... Sometimes it's nice just to be curious.
In that regard, the researchers who recreated a 3,000-Year-Old Egyptian mummy's voice might "take the cake" (or "drop the mic").
The mummy's name is Nesyamun. They used a 3D printer and an electronic larynx to create the sound. They didn't recreate his tongue - so his voice doesn't take that into account. From what I can tell, all they've gotten "him" to say is "ehh". Very mummy-like.
An engineer and oceanographer, Derya Akkaynak, created an algorithm that removes the water from underwater images - meaning it takes away the haze & tint that come with most underwater photos. It doesn't require a color chart either (though it does need distance information it gathers through numerous photographs from different angles).
The Sea-thru method estimates backscatter using the dark pixels and their known range information. Then, it uses an estimate of the spatially varying illuminant to obtain the range-dependent attenuation coefficient. Using more than 1,100 images from two optically different water bodies, which we make available, we show that our method with the revised model outperforms those using the atmospheric model. Consistent removal of water will open up large underwater datasets to powerful computer vision and machine learning algorithms, creating exciting opportunities for the future of underwater exploration and conservation.
Essentially, the algorithm goes through every pixel and color balances the image based on collected data on distance/color degradation.
As with most algorithms of this type - the more data we feed it, the better it gets. Sea-thru already has great applications for furthering ocean-based research, but the follow-up question is can this algorithm be extrapolated outward to deal with other atmospheric conditions outside of water - smog, etc.
What other uses can you imagine? It is not hard to imagine how this could be applied to market data either ... Interesting stuff!
AI has plenty of weaknesses - I've talked about some before, and I'll continue to talk about them in the future, but two specific weaknesses were brought to my attention this week.
AI Portraits - Won't Steal Your Data, But Might Steal Your Soul Dorian Gray-Style
I assume most of you have seen the FaceApp trend - people age-ifying their photos and unwittingly giving the rights to their photos to a shadowy Russian tech company. You've also likely seen AI paintings selling for ridiculous money.
But have you seen their lovechild AI Portraits - a more wholesome experiment run by the MIT-IBM Watson AI Lab. AI Portraits uses approximately 45,000 different Renaissance-esque 15th-century portraits and General Adversarial Networks to translate your selfie into an artistic masterpiece. It's novel because instead of simply drawing over your face it's generating new features and creating an entirely new version of your face.
Mauro Martino via YouTube
It's impressive because it determines the best style for your portrait based on your features, your background, and more.
However, it's not without "flaw". The choice of 15th-century portraiture creates a couple of clear biases. At the time, portraits of smiling or laughing individuals were rare, so your smile will likely not transfer. As well, there's a clear bias towards anglo-saxonification.
My son got excited while playing with the app and sent several of his coworkers, friends, and family through the app. If you look at the bottom right, you'll see my lovely wife Jen's portrait.
Most of you have seen my wife and know that she is Indonesian, something that is very much removed from the translation.
All photos are immediately deleted from their servers after creating your image, so your privacy is safe (this time!)
All biases can be considered quirks of this current iteration of the program - which I do earnestly believe is interesting.
Later, you can imagine an AI choosing between various different styles of art based on a cornicopia of factors - or off human selection - but you have to walk before you can run, and this is a fun way to get people excited about AI.
Computer Answering Systems - No, The Answer Isn't 42
“Yes…Life, the Universe, and Everything. There is an answer. But I’ll have to think about it...the program will take me seven-and-a-half million years to run.” - Deep Thought, Hitchhiker's Guide To The Galaxy
Think of the global excitement when IBM's Watson first beat Ken Jennings in Jeopardy ... it's widely considered one of the holy grails of AI research to create a machine that truly understands the nuances of language and human thought. Yet, if you've talked to Alexa recently, you know there's a long way to go.
Today's question answering systems are basically glorified document retrieval systems. They scan text for related words and send you the most relevant options. Researchers at the University of Maryland recently figured out how to easily create questions that stump AI (without being paradoxical, impossible to answer, requiring empathy etc.) in order to enhance those systems.
A system that understands those questions will be a massive step toward a real understanding and processing of language.
So what's the secret to these "impossible" questions?
The questions revealed six different language phenomena that consistently stump computers. These six phenomena fall into two categories. In the first category are linguistic phenomena: paraphrasing (such as saying “leap from a precipice” instead of “jump from a cliff”), distracting language or unexpected contexts (such as a reference to a political figure appearing in a clue about something unrelated to politics). The second category includes reasoning skills: clues that require logic and calculation, mental triangulation of elements in a question, or putting together multiple steps to form a conclusion [...]
For example, if the author writes “What composer's Variations on a Theme by Haydn was inspired by Karl Ferdinand Pohl?” and the system correctly answers “Johannes Brahms,” the interface highlights the words “Ferdinand Pohl” to show that this phrase led it to the answer. Using that information, the author can edit the question to make it more difficult for the computer without altering the question’s meaning. In this example, the author replaced the name of the man who inspired Brahms, “Karl Ferdinand Pohl,” with a description of his job, “the archivist of the Vienna Musikverein,” and the computer was unable to answer correctly. However, expert human quiz game players could still easily answer the edited question correctly.
The main change is increasing the complexity of the questions by nestling another question. In the above example, the second question forces the AI not only to decide the composer inspired by Karl Ferdinand Pohl, but also to decipher who is inspiring (hint: It's Karl Ferdinand Pohl).
AI isn't great yet at mental triangulation; at putting together multiple steps to form a conclusion. While AI is great at brute force applications - we're still coding the elegance.
I went to Havana with a diverse group of business people, financial professionals and representatives from the US Fed.
Here is a photo taken with some of the classic cars that proudly dominate the roads despite cheaper Russian and Chinese alternatives.
The city was beautiful … dirty and broken, for sure … but still beautiful. Here is a view from my hotel room.
I commented that it was almost like seeing a severely wounded elephant. You can tell that it's hurt (and barely a shadow of its old self). Nevertheless, you can see the amazing bone structure. It is easy to imagine what it once was.
In Cuba, the geography and the architecture are amazing. However, money hasn't been spent on the upkeep. Even though people live there, it seems surreal (almost like a post-apocalyptic wasteland).
In the story of Exodus, the Jews spent 40 years wandering the desert after escaping from Egypt. That means two generations of people, who didn't remember life as slaves, were ultimately the ones who entered the “Promised Land”.
On some level, that's how Cuba is now. Most inhabitants weren’t born (or can’t remember) the 1960s. They have known nothing but this.
Cuba is an interesting place … and I’d bet that it has an interesting future.
The “lack” had a side effect. It produced a mutation. A portion of society grew more resourceful and resilient.
Like natural selection … nature finds a way.
The rules change, the players change, even the game itself changes ... That is how new ideas and new leaders emerge.
Sometimes, almost no one notices. Sometimes they do.
Here Are Some Links For Your Weekly Reading - January 19th, 2020
Here are some of the posts that caught my eye recently. Hope you find something interesting.
Lighter Links:
Trading Links:
Posted at 12:23 PM in Art, Business, Current Affairs, Gadgets, Games, Healthy Lifestyle, Ideas, Just for Fun, Market Commentary, Personal Development, Science, Television, Trading, Trading Tools, Web/Tech | Permalink | Comments (0)
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