WTF Fun Fact 13536 – Digitizing Smell

In order to smell, our brains and noses have to work together, so the idea of digitizing smell seems pretty “out there.”

However, if you think about it, our noses are sensing molecules. Those molecules can be identified by a computer, and the smells the humans associated with them can be cataloged. It’s not quite teaching a computer to smell on its own, but maybe it’s best we don’t give them too many human abilities.

The Enigma of Olfaction

While we’ve successfully translated light into sight and sound into hearing, decoding the intricate world of smell remains a challenge.

Olfaction, compared to our other senses, is mysterious, diverse, and deeply rooted in both emotion and memory. Knowing this, can we teach machines to interpret this elusive sense?

Digitizing Smell

A collaboration between the Monell Chemical Senses Center and the startup Osmo aimed to bridge the gap between airborne chemicals and our brain’s odor perception. Their objective was not just to understand the science of smell better but to make a machine proficient enough to describe, in human terms, what various chemicals smell like.

Osmo, with roots in Google’s advanced research division, embarked on creating a machine-learning model. The foundation of this model was an industry dataset, which detailed the molecular structures and scent profiles of 5,000 known odorants.

The idea? Feed the model a molecule’s shape and get a descriptive prediction of its smell.

That might sound simple, but the team had to make sure they could ensure the model’s accuracy.

The Litmus Test: Man vs. Machine

To validate the machine’s “sense of smell,” a unique test was devised.

A group of 15 panelists, trained rigorously using specialized odor kits, was tasked with describing 400 unique odors. The model then predicted descriptions for the same set.

Astonishingly, the machine’s predictions often matched or even outperformed individual human assessments, showcasing its unprecedented accuracy.

Machines That Can ‘Smell’ vs. Digitizing Smell

Beyond its core training, the model displayed unexpected capabilities. It accurately predicted odor strength, a feature it wasn’t explicitly trained for, and identified distinct molecules with surprisingly similar scents. This accomplishment suggests we’re inching closer to a world where machines can reliably “smell.”

But for now, that’s overstating it. The team has made a major leap towards digitizing smell. But machines don’t have senses. They can only replicate the kind of information our brains produce when we smell things. Of course, they don’t have any sense of enjoyment (or repulsion) at certain smells.

In any case, the Monell and Osmo collaboration has significantly advanced our journey in understanding and replicating the sense of smell. As we move forward, this research could revolutionize industries from perfumery to food and beyond.

 WTF fun facts

Source: “A step closer to digitizing the sense of smell: Model describes odors better than human panelists” — Science Daily

WTF Fun Fact 13501 – Google, Apple, Intel, Adobe Lawsuit

The Google, Apple, Intel, Adobe lawsuit is a sinister and embarrassing moment in tech history – one that the corporate giants had to pay for.

In the early 2010s, it came to light that some of these tech giants were involved in secret anti-poaching agreements. Leading companies like Google, Apple, Intel, and Adobe had clandestine arrangements not to hire each other’s employees. This essentially froze salaries by eliminating the competition for top talent. What ensued was a scandal and a class action lawsuit that exposed the dark side of Silicon Valley.

The Roots of the Apple, Google, Intel, Adobe Lawsuit

The roots of the issue began with individual agreements. The earliest known pact was between Pixar and Lucasfilm in 1986, which agreed not to poach each other’s employees and to cap wages. Yet, by the 2000s, other Silicon Valley heavyweights had entered into similar agreements. Google and Apple had their secret deal, as did Google and Intel, Google and Intuit, and so on.

These agreements were not merely handshake deals. Emails and written correspondence showed the top executives of these companies actively reinforcing the non-poaching pacts. For instance, an email from Steve Jobs to Sergey Brin explicitly warned Google against recruiting Apple’s team.

The effect of these agreements was suppressed wage growth for employees. As a result, engineers, developers, and other tech professionals were unknowingly restricted in their career opportunities. Without the ability to get counter-offers or even entertain offers from a significant portion of the leading companies, many employees lost out on potential salary hikes, better positions, and more promising career trajectories.

The Class Action Lawsuit

In 2011, the issue reached a critical point. Over 64,000 employees filed a class-action lawsuit against Adobe, Apple, Google, Intel, Intuit, Lucasfilm, and Pixar. The suit claimed that these companies conspired to eliminate competition for skilled labor, thus suppressing wage growth.

The plaintiffs alleged that the lost wages due to this collusion amounted to billions of dollars. To back their claims, they pointed to emails and other communications between CEOs like Steve Jobs of Apple and Eric Schmidt of Google, which showed that these leaders were actively enforcing these agreements.

Regulatory Scrutiny and Settlement of The Apple, Google, Intel, Adobe Lawsuit

The Department of Justice (DOJ) took notice of these agreements. In 2010, they announced a settlement with six of these companies. As per the settlement, the companies agreed to a prohibition against engaging in any anti-poaching agreements for a duration of five years. However, the DOJ’s settlement didn’t provide any compensation to the affected employees. This is what led to the class action lawsuit in 2011.

After a series of legal processes, in 2014, the companies tried to settle the lawsuit for $324.5 million. However, this amount was rejected by the judge for being too low. As a result, in 2015, the companies increased their offer and agreed to a settlement of $415 million, which employees eventually accepted.

Reflection and Legacy

The unfolding of this scandal delivered a pivotal lesson about the necessity of ethical corporate practices.

The power that these tech titans wield, in terms of shaping industry dynamics and affecting the lives of thousands of professionals, was laid bare. As behemoths in the technological realm, their actions have vast repercussions, and the anti-poaching agreements betrayed the trust many had placed in them.

 WTF fun facts

Source: “Tech Giants Will Pay $415 Million To Settle Employees’ Lawsuit” — All Tech Considered

WTF Fun Fact 13449 – How Google reCAPTCHA works

Do you know how Google reCAPTCHA works? Maybe you’ve thought about it if you’ve ever been annoyed at having to prove to a machine that you’re human.

How Google reCAPTCHA works?

Google’s reCAPTCHA is a type of CAPTCHA, an acronym that stands for Completely Automated Public Turing test to tell Computers and Humans Apart. By serving as a litmus test for human-like interaction, CAPTCHAs are designed to protect websites against spam and online fraud. However, the “I am not a robot” prompt is far more than your run-of-the-mill CAPTCHA.

This advanced version does not solely rely on deciphering distorted text or identifying objects within images. When you click on that “I am not a robot” box, a risk analysis engine kicks into gear. It considers numerous factors that distinguish humans from bots.

This system notes the time it takes to interact with the checkbox and your IP address. It even tracks the peculiarities of your mouse movements. The mechanics of how you type, known as keystroke dynamics, is another vital piece of data used in this process.

All these factors collaborate to create a risk profile, allowing reCAPTCHA to make an informed decision about your human-ness.

Why clicking the box doesn’t prove you’re human

However, it’s worth addressing a common myth here. Some believe that when they engage with the “I am not a robot” checkbox, reCAPTCHA goes through their browsing history. It’s true that reCAPTCHA collects certain user data like cookies for abuse detection and prevention. However, it doesn’t comb through your individual browsing history. Google, the provider of reCAPTCHA, has robust privacy measures to ensure user data isn’t misused.

But that’s not to say that reCAPTCHA doesn’t consider your past interactions. As part of Google’s services, it can use cookies and session data to understand if you’ve frequently interacted with CAPTCHAs in the past. This information can influence the risk analysis engine’s decision-making (but it’s a far cry from inspecting your browsing history).

As we’ve uncovered, the “I am not a robot” checkbox is more than a simple statement. It’s a potent piece of technology.

As we continue to use the internet , it’s vital to understand these unseen mechanisms.

 WTF fun facts

Source: “People Are Just Now Learning How The “I Am Not A Robot” Captcha Test Actually Works” — IFL Science

WTF Fun Fact 13302 – Bug Bounty Programs

Have you heard of “bug bounty programs”? No, they’re not about capturing critters in your yard. These programs are run by major tech companies. Companies like Google, Microsoft, and Facebook use these programs to incentivize hackers and security researchers to find and report vulnerabilities in their systems by offering rewards or cash bounties.

Big Tech’s bug bounty programs

Bug bounty programs allow tech companies to identify and address security weaknesses. But more importantly, they do so before the weaknesses can be exploited by cybercriminals. Some programs have paid out millions to researchers and hackers who found major vulnerabilities. For example, in 2019, Google paid out over $6.5 million in bug bounties to people around the world.

Bug bounty programs typically have guidelines and rules. These outline what types of vulnerabilities are eligible for rewards and how they should be reported. Once a researcher or hacker identifies a vulnerability, they submit it to the company’s bug bounty program. The company then verifies the bug and determines if it is eligible for a reward. If the vulnerability is valid, the company forks over the reward to the person who reported it.

Some companies may also offer other incentives, such as swag or recognition. This helps encourage participation. Some programs may even have different reward tiers for different types of vulnerabilities. For example, more critical or severe vulnerabilities earn higher payouts.

A win-win solution for cybersecurity

There are several reasons why companies use these programs. Identifying security vulnerabilities before they can be exploited by cybercriminals saves the company from potential data breaches, financial losses, and reputational damage.

The programs also allow companies to work with the security community. This helps them improve their security measures and stay ahead of emerging threats. These programs are also cost-effective. Companies discover security weaknesses, as they only pay for valid bugs that are reported.

 WTF fun facts

Source: “Google paid $6.7 million to bug bounty hunters in 2020” — ZDNet

WTF Fun Fact 13107 – Google Backrub

You may know part of the the story of Larry Page and Sergey Brin, the founders of Google. They met on a tour of Stanford, when Brin was showing prospective grad student Page around. While they didn’t agree on anything at first, they eventually became friends and business partners and invented Google. Except there was a step before Google – Backrub.

From Backrub to Google

According to Google’s own page on their history, the men wanted to build “a search engine that used links to determine the importance of individual pages on the World Wide Web. They called this search engine Backrub.”

So…eww. Can you imagine saying, “I don’t know, I’ll need to backrub that information?”

We don’t know the precise details about why they changed the name. But we know how the word Google came to be.

“The name was a play on the mathematical expression for the number 1 followed by 100 zeros and aptly reflected Larry and Sergey’s mission ‘to organize the world’s information and make it universally accessible and useful.'”

Google was a big deal in the academic community at first. Then it caught the eye of Silicon Valley investors in the late 90s.

“In August 1998, Sun co-founder Andy Bechtolsheim wrote Larry and Sergey a check for $100,000, and Google Inc. was officially born. With this investment, the newly incorporated team made the upgrade from the dorms to their first office: a garage in suburban Menlo Park, California, owned by Susan Wojcicki (employee #16 and now CEO of YouTube). Clunky desktop computers, a ping pong table, and bright blue carpet set the scene for those early days and late nights.”

Google grows

Keeping things useful but unconventional was the duos brand style. Do you remember the first Google Doodle in 1998? It was a stick figure inside the logo telling everyone the staff was off-site attending Burning Man.

How about their motto? “Don’t be evil.”

In any case, things are now a far cry from the days of Backrub.  WTF fun facts

Source: “From the garage to the Googleplex” — Google

WTF Fun Fact 12429 – The Inspiration for Google Image Search

Now known as Google Images, the idea behind the Google Image Search feature was none other than the pop star and actress Jennifer Lopez. When she worse the deep v-cut Versace dress to the Grammys in February of 2000, people performed millions of Google searches to get a second look at it.

Searches for the dress continued at a surprising rate throughout the year and into 2001. As a result, Google made it possible to search images alone starting on July 12, 2001. Before this, you could only search text on websites.

The feature was created by engineer Huican Zhu and product manager Susan Wojcicki (who is now the current CEO of YouTube). In 2001, 250 million images were indexed in Image Search. By 2010, it contained 10 billion photos.

The story has been confirmed by Eric Schmidt, who was the executive chairman of Google at the time.

In an essay published on Project Syndicate, he wrote: “At the time, it was the most popular search query we had ever seen. But we had no surefire way of getting users exactly what they wanted: J.Lo wearing that dress.” As a result, “Google Image Search was born.” – WTF Fun Facts

Source: “How Jennifer Lopez’s infamous 2000 Grammys dress — which was unretired this week — inspired Google image search” — Business Insider