Trending February 2024 # Ai Can Help Fight Climate Change—But It Can Also Make It Worse # Suggested March 2024 # Top 8 Popular

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Modern technology certainly has a massive role to play in the fight against climate change. Solar panels, wind turbines and electric vehicles often take center stage. Still, there’s one more technology that isn’t so often discussed in the climate realm that could play a major role in the fight against climate change: Artificial intelligence. 

Artificial intelligence is an algorithm-driven system that can do everything from curate your social media feed to drive a car autonomously. Each type of artificial intelligence is designed for its own purpose, and many researchers are looking at how it could be used to both help us fight climate change and be better prepared to adapt to its effects. 

Priya Donti, co-founder and chair of an organization called Climate Change AI that fosters the use of AI to solve climate-related problems, tells Popular Science that her group is focused on helping people with backgrounds in AI, climate science, public policy and more come together to see how AI could help us in the climate fight.

“When we think about AI, we should think about the fact that it’s a general purpose technology that can be used for many different kinds of applications,” Donti says. “These include applications that are good for climate action, such as optimizing electric power grids in order to foster the integration of renewable energy or collecting information about building footprints from satellite imagery in order to shape energy efficiency policies.”

Climate Change AI runs educational events and workshops, but it also awards researchers with grants. The organization awarded $2 million in grants to 13 projects in April ranging from using AI to estimate ice volume in glaciers to using it to analyze power grids. 

Donti says AI is not some kind of “silver bullet” in the fight against climate change, but it’s an additional tool. One of the most exciting ways to use AI is to speed up scientific research that could lead to the development of even more tools for fighting climate change. Artificial intelligence systems could be used to give scientists a better idea of where to take their research so they don’t have to spend so much time trying out different ideas.

“AI and machine learning have started to be used to actually analyze the outcomes of past scientific and engineering experiments and recommend from those which experiment is the most fruitful to try next,” Donti says.

[Related: How AI could help bring a sustainable reckoning to hydropower.]

Instead of a scientist trying out dozens of possible next-generation battery chemistries, for example, a well-designed AI system could tell them that only three of those chemistries are actually worth pursuing. That could save them time and reduce the cost of research. A company called Aionics has already started to help researchers use AI in this way. 

All of that said, AI isn’t exclusively a force for good. Donti says it can also be used in ways that harm the planet, such as oil companies using it to accelerate oil and gas exploration and extraction. Shell Oil has been a major proponent of AI. Furthermore, Donti says people in this part of the tech world need to be careful to consider how they’re using AI and who benefits from its use.

“AI is an accelerator of the systems in which it’s employed. If you employ it in an inequitable system or employ it to optimize the wrong thing, it’s just going to make those problems worse,” Donti says. “There are lots of ways in which AI and equity intersect that are worth thinking about. Likewise, there are lots of ways climate change and equity are deeply intertwined.”

It’s important to consider how AI can be beneficial for those who are most threatened by climate change and have the fewest resources, Donti says. It is crucial to make sure it’s not utilized in ways that would benefit those with resources at the cost of those without them. Biased AI systems have been found to further racial and economic inequities in the past. 

“AI and machine learning algorithms are not in any way objective. They definitely inherit the value systems and priorities associated explicitly or implicitly with the data they’re given and the problems they’re meant to solve,” Donti says.

AI isn’t perfect—and we’ll likely never get the perfect answer to our climate dilemmas from it. However, it could be used to accelerate research, analyze energy resources, generate forecasts, monitor the planet as it changes and more. 

You're reading Ai Can Help Fight Climate Change—But It Can Also Make It Worse

Climate Change Could Make Severe Turbulence Even Worse

Climate change makes severe turbulence more likely. Sofia Sforza via Unsplash

Airplane passengers are in for an increasingly bumpy ride according to a study released today in the journal Advances in Atmospheric Sciences. Climate change is altering the jet stream, making severe turbulence more likely. The study builds on earlier work which found that climate change would lead to bumpier airplane rides. What makes the new research unique is that it quantifies how much different kinds of turbulence will increase—59 percent in the case of light turbulence, a 94 percent increase in moderate turbulence, and 149 percent increase in severe turbulence.

For the one in four Americans who are afraid of flying, any jostling could be considered severe. But like an earthquake, turbulence is rated on a scale. One is light—gentle enough so passengers may not notice it—three is moderate, or enough to jostle a drink, five is severe, and seven is extreme.

“Anything above five is by definition stronger than gravity,” says study author Paul Williams, an atmospheric scientist at the University of Reading in the United Kingdom. “What that means is that anything that’s not strapped in will potentially be projected around inside the plane. That would include passengers.”

Shake, Rattle, But No Rolls

Turbulence happens when an air mass moving at one speed meets another air mass moving at a different speed. The meeting causes a sudden shift in airflow, leading air to move chaotically. It’s a bit like trying to walk down the street on a particularly windy day, and being buffeted about in multiple directions. So, a plane moving into turbulent air may have its left wing hit by an upward gust causing the plane to bank right. Similarly, if both wings are suddenly hit by a downward gust, the whole plane might drop a bit, which isn’t great for anyone inside.

Last October, an Air New Zealand flight from Ho Chi Minh to Auckland encountered turbulence so severe it was forced to turn around after two crew members suffered critical injuries. That same year, a JetBlue flight from Boston to Sacramento was forced to make an unplanned landing after it hit a patch of turbulence that sent 22 passengers and 2 crew members to the hospital. In 2024, an Air Canada flight from Toronto to Shanghai experienced turbulence that led to the injuries of 21 people. The plane made an emergency landing in Calgary, Alberta. And in 2014, a United Airlines flight from Denver to Billings, Montana hit turbulence so severe that five people went into the hospital.

Satellite observations dating back to the 1970s show that because of climate change, different parts of the atmosphere are warming up at different rates. At 30-40,000 feet, the low latitude tropical regions are warming much faster than the high latitude arctic regions (which is the opposite of what’s happening on the ground). This temperature difference has always driven the jet stream, but as tropical regions warm up faster than the arctic, that difference grows—and the jet stream becomes both stronger, and less stable. Turbulence is coming along for the ride.

“Turbulence can actually damage planes,” said Williams. “There was a plane flying over the Colorado Rocky’s on the 9th of December 1992 through some extreme clear air turbulence—it would have been a seven [on the scale]. Six meters of the left wing broke off and one of the engines got torn off as well.”

Plane engines, Williams told PopSci, are affixed with aptly named, ‘shear nuts and bolts.’ The engines are designed to shear off planes if they become unstable. “The fact that the engine broke off probably saved the life of the people on the plane, because the last thing you want is an unstable engine kind of hanging off a plane causing instabilities.”

This kind of damage is rare—in most cases turbulence is still more about comfort than safety, and there hasn’t been a single plane crash due to turbulence since the 1960s. But even light and moderate turbulence will cause wear and tear on a plane. That means the need for inspections—for planes to be taken out of service and maintained—will also go up. It’s a significant economic burden for an industry already operating on razor thin margins.

While the seasoned traveler may wonder why pilots don’t just fly around the turbulence, the answer is simple: the pilots can’t see it. Though we tend to think of turbulence as being associated with storms, the kind of turbulence Williams focuses on is related not to weather but to the jet stream, or the bands of strong wind in the upper levels of the atmosphere.

“We call it clear air turbulence to distinguish it from the other kinds of turbulence which is in clouds,” said Williams. “The pilot can see the clouds, so he or she knows that the turbulence will be there and will avoid trying to fly through. But clear air turbulence is particularly hazardous precisely because it’s invisible. It tends to strike when the seatbelt light is switched off and passengers are moving around inside the cabin.” On average, patches of clear air turbulence tend to be more than half a mile tall (3,280 feet) and 37 miles wide.

Clear air turbulence is particularly dangerous since pilot’s can’t see it coming. Pexels

Predicting Turbulence

Williams was able to predict increases in turbulence by running a climate model. He ran it first under control conditions, using preindustrial levels of carbon dioxide for the equivalent of twenty years. He then ran a second simulation where the CO2 is double that of the pre-industrial levels—roughly where we’ll be by the middle of the century if we don’t change our behaviors.

But climate models don’t actually have this kind of turbulence built into them. “Williams took 21 vetted, commonly used indicators for turbulence and looked for those in the climate model,” said Kristopher Karnauskas, a researcher in the Department of Atmospheric and Oceanic Sciences at the University of Colorado Boulder who was not involved in the study. “It’s not just limited to one predictor of turbulence, because no one predictor of turbulence is perfect or always right, so he used a broad ensemble approach.”

Williams then compared the control run with the elevated CO2 condition and calculated the amount of turbulence in both of them. That’s how he found the increases.

Climate change will increase turbulence by a lot. Kendra Pierre-Louis

Why Models Matter

Climate models have come under fire recently, in part because to lay people they can seem disconnected from reality. That’s why Karnauskas likes to use TV screens to explain how they work.

“With a climate model, you take the planet and you cut it up into grid cells like the pixels on a TV,” Karnauskas. “Each of those grid cells knows all the laws of physics. It looks at its neighbors around it and says ‘is it warm over there, is the wind coming from this direction, and then it marches forward in time.” By being fed those base conditions, the model can make extrapolations about the future.

In fact, the only limitation of the study that Karnauskas notes is that it only uses one climate model, which he says limits our ability to categorize the full certainty of the results. But this isn’t the first study to suggest that the jet stream is changing along with the warming climate.

Both Williams and Karnauskas have published studies that found that because the jet stream is getting stronger, eastbound flights from the U.S. to Europe will get faster, while westbound flights from Europe will be slower. This is backed up by real world incidents.

It’s important to note that Williams’ study only looked at the North Atlantic—its conclusions can’t be extrapolated for other routes. At the same time, however, it’s important to recognize the impacts that climate change will have on the aviation industry so that companies can better plan and prepare for everything from plane maintenance and repair to fueling.

“For decades, all of the focus on climate change and air travel was about how air travel is going to make climate change worse,” said Karnauskas. “But this kind of study, and other studies around climate change making flight times longer, are a new wave of looking at that relationship. It’s showing that climate change can feed back on the industry itself. It’s not just that air travel affects climate—we know that’s true. But air travel is being affected by climate change.”

Ai Can Help Predict March Madness Upsets, But It’s Far From Perfect

“Beware the Ides of March.” Yes, it’s finally that time of year again: when the emperors of college basketball must watch their backs, lest the lowly bottom seeds of the tournament strike.

Before March 15, millions around the world filled out their March Madness brackets. In 2023, ESPN received a record 18.8 million brackets.

The first step to a perfect bracket is correctly choosing the first round. Unfortunately, most of us can’t predict the future. Last year, only 164 of the submitted brackets were perfect through the first round—less than 0.001 percent.

Many brackets are busted when a lower-seeded team upsets the favored higher seed. Since the field expanded to 64 teams in 1985, at least eight upsets occur on average each year. If you want to win your bracket pool, you better pick at least a few upsets.

We’re two math Ph.D. candidates at the Ohio State University who have a passion for data science and basketball. This year, we decided it would be fun to build a computer program that uses a mathematical approach to predict first-round upsets. If we’re right, a bracket picked using our program should perform better through the first round than the average bracket.

Fallible humans

It’s not easy to identify which of the first-round games will result in an upset.

Say you have to decide between the No. 10 seed and the No. 7 seed. The No. 10 seed has pulled off upsets in its past three tournament appearances, once even making the Final Four. The No. 7 seed is a team that’s received little to no national coverage; the casual fan has probably never heard of them. Which would you choose?

If you chose the No. 10 seed in 2023, you would have gone with Virginia Commonwealth University over Saint Mary’s of California—and you would have been wrong. Thanks to a decision-making fallacy called recency bias, humans can be tricked into to using their most recent observations to make a decision.

Recency bias is just one type of bias that can infiltrate someone’s picking process, but there are many others. Maybe you’re biased toward your home team, or maybe you identify with a player and desperately want him or her to succeed. All of this influences your bracket in a potentially negative way. Even seasoned professionals fall into these traps.

Modeling upsets

Machine learning can defend against these pitfalls.

In machine learning, statisticians, mathematicians and computer scientists train a machine to make predictions by letting it “learn” from past data. This approach has been used in many diverse fields, including marketing, medicine, and sports.

Machine learning techniques can be likened to a black box. First, you feed the algorithm past data, essentially setting the dials on the black box. Once the settings are calibrated, the algorithm can read in new data, compare it to past data and then spit out its predictions.

A black box view of machine learning algorithms. Matthew Osborne, CC BY-SA

In machine learning, there are a variety of black boxes available. For our March Madness project, the ones we wanted are known as classification algorithms. These help us determine whether or not a game should be classified as an upset, either by providing the probability of an upset or by explicitly classifying a game as one.

Our program uses a number of popular classification algorithms, including logistic regression, random forest models and k-nearest neighbors. Each method is like a different “brand” of the same machine; they work as differently under the hood as Fords and Toyotas, but perform the same classification job. Each algorithm, or box, has its own predictions about the probability of an upset.

We used the statistics of all 2001 to 2023 first-round teams to set the dials on our black boxes. When we tested one of our algorithms with the 2023 first-round data, it had about a 75 percent success rate. This gives us confidence that analyzing past data, rather than just trusting our gut, can lead to more accurate predictions of upsets, and thus better overall brackets.

Chances of an upset

For March Madness 2023, three machine learning models attempt to predict whether there will be an upset in the first round. The percentages are the probability that the match up results in a lower-seeded team beating a higher-seeded team.

SEEDING MATCH UP HIGHER SEED LOWER SEED MODEL A MODEL B MODEL C ACTUAL GAME OUTCOME

# 1 vs # 16 Virginia UMBC 2.81% 10% Not an Upset Upset

# 8 vs # 9 Creighton Kansas State 30.69% 10% Not an Upset Not an Upset

# 5 vs # 12 Kentucky Davidson 26.07% 60% Upset Not an Upset

# 4 vs # 13 Arizona Buffalo 23.46% 60% Not an Upset Upset

# 6 vs # 11 Miami (FL) Loyola-Chicago 31.65% 10% Not an Upset Upset

# 3 vs # 14 Tennessee Wright State 11.03% 0% Not an Upset Not an Upset

#7 vs # 10 Nevada Texas 40.76% 70% Not an Upset Not an Upset

# 2 vs # 15 Cincinnati Georgia State 9.96% 50% Not an Upset Not an Upset

# 1 vs # 16 Xavier Texas Southern 8.17% 0% Not an Upset Not an Upset

# 8 vs # 9 Missouri Florida State 56.17% 40% Upset Upset

# 5 vs # 12 Ohio State South Dakota State 17.86% 10% Upset Not an Upset

# 4 vs # 13 Gonzaga UNC Greensboro 11.91% 40% Not an Upset Not an Upset

# 6 vs # 11 Houston San Diego State 33.6% 50% Upset Not an Upset

# 3 vs # 14 Michigan Montana 4.91% 20% Not an Upset Not an Upset

#7 vs # 10 Texas A&M Providence 42.96% 10% Not an Upset Not an Upset

# 2 vs # 15 UNC Lipscomb 6.38% 10% Not an Upset Not an Upset

# 1 vs # 16 Villanova Radford 2.58% 40% Not an Upset Not an Upset

# 8 vs # 9 Virginia Tech Alabama 42.82% 40% Upset Upset

# 5 vs # 12 WVU Murray State 9.88% 10% Not an Upset Not an Upset

# 4 vs # 13 Wichita State Marshall 18.59% 20% Not an Upset Upset

# 6 vs # 11 Florida St. Bonaventure 14.53% 40% Not an Upset Not an Upset

# 3 vs # 14 Texas Tech Stephen F. Austin 7.97% 0% Not an Upset Not an Upset

#7 vs # 10 Arkansas Butler 33.29% 20% Not an Upset Upset

# 2 vs # 15 Purdue Cal State Fullerton 4.07% 0% Not an Upset Not an Upset

# 1 vs # 16 Kansas Upenn 5.91% 0% Not an Upset Not an Upset

# 8 vs # 9 Seton Hall NC State 36.80% 40% Not an Upset Not an Upset

# 5 vs # 12 Clemson New Mexico 22.93% 40% Not an Upset Not an Upset

# 4 vs # 13 Auburn Charleston 16.51% 30% Not an Upset Not an Upset

# 6 vs # 11 TCU Syracuse 28.83% 10% Not an Upset Upset

# 3 vs # 14 Michigan State Bucknell 7.39% 20% Not an Upset Not an Upset

#7 vs # 10 Rhode Island Oklahoma 59% 40% Upset Not an Upset

# 2 vs # 15 Duke Iona 5.35% 10% Not an Upset Not an Upset

Model C: K Nearest Neighbors Classification

Chart: Matthew Osborne and Kevin Nowland, The Conversation, CC-BY-ND Get the data

That’s not to say that machine learning will give us perfect brackets. Even though the box bypasses human bias, it’s not immune to error. Results depend on past data. For example, if a No. 1 seed were to lose in the first round, our model would not likely predict it, because that has never happened before.

(Editor’s note: LOL)

Additionally, machine learning algorithms work best with thousands or even millions of examples. Only 544 first-round March Madness games have been played since 2001, so our algorithms will not correctly call every upset. Echoing basketball expert Jalen Rose, our output should be used as a tool in conjunction with your expert knowledge—and luck!—to choose the correct games.

Machine learning madness?

We’re not the first people to apply machine learning to March Madness and we won’t be the last. In fact, machine learning techniques may soon be necessary to make your bracket competitive.

You don’t need a degree in mathematics to use machine learning—although it helps us. Soon, machine learning may be more accessible than ever. Those interested can take a look at our models online. Feel free to explore our algorithms and even come up with a better approach yourself.

Matthew Osborne is a Ph.D Candidate in Mathematics, and Kevin Nowland is a Ph.D Candidate in Mathematics at The Ohio State University. This article was originally featured on The Conversation.

How Google’s Experimental Apps Can Help You Fight Digital Addiction

Google is known for constantly bringing new apps to life. Some of them are just useful tools that are aimed at making your digital life easier. Others are more artsy and creative. 

This time Google has released a rather specific batch of new apps. They are experimental and their main focus is on curing your digital addiction. 

Table of Contents

In case you decide to test all of the Google experimental apps yourself after reading about them, make sure to use one of these free tools that reduce digital eye strain. All the extra time spent staring at the glaring screen won’t do any good for your eyes or for your sleep. 

Our Verdict: a top pick if you’re looking to really cure your smartphone addiction.

First up is a productivity app called Morph. Definitely worth a try if you have issues getting distracted with social media and entertainment apps at work.

You can set up multiple versions of your home screen with different sets of apps. Choose carefully though, as during that set time period you won’t be getting notifications from any of the apps that you didn’t select. 

One more pretty cool perk that Morph comes with is connecting to your location. For example, you can set a GPS location for your working out mode and it will automatically turn it on once you get to the gym. 

Our Verdict: the one with the most potential.

Even when you decide to not touch your phone for the next couple of hours, you can be easily tempted by a notification sound. They’re very distracting and play a major part in aiding your digital addiction.

With Post Box, you can turn off instant notifications and set it up to be delivered in batches. You can choose up to four different time slots a day, and your notifications will be delivered all at once. 

One downside is that at the moment you can’t customise the notification delivery times and have to stick with the four options available on the app. 

Post Box can be a good way to keep up with your social life in a more organized manner. If that sounds like something you struggle with, you might also want to try one of the free calendar apps for Android. 

Our Verdict: your perfect “slap on the wrist”. 

Unlock Clock is essentially a live wallpaper that shows you how many times you’ve unlocked your smartphone during the day. After you install it, set it as your wallpaper. Then on your home screen you’ll see a giant number that will remind you just how much you rely on your smartphone for…pretty much everything.

The giant number on your screen can serve as a wake-up call for anyone who is not aware of how much time they spent staring at their phone’s screen. The number resets each day. You can set a goal to minimize your smartphone use and then see how many days it takes you to reach it. 

Use Unlock Clock as a social experiment with friends on a night out. See how many times each of you unlock their gadgets and maybe even turn it into a competition. Let the “loser” pick up the tab in the end of the night. That should teach them! 

Our Verdict: a fun little game to play with friends.

It’s a proven scientific fact that if you want to start training, it works better if you bring a buddy to the gym to train with you (or you can use one of the free fitness apps for motivation). So why not make your friends go through a digital detox with you as well? We Flip will help you make it more fun and maybe even turn it into a competition.

The way the Google experimental app works is, in a group of people you pair your phones together. When you “flip the switch” a new session starts. Then if/when someone unlocks their phone, the session ends and gives you the stats on how you did as a group. 

You can raise the stakes by turning it into a bet – whoever causes the session to end has to buy the next round. Or lose their phone privileges for the night (a hardcore option for the daredevils among us). 

Our Verdict: recommended for fans of the team-building game of the same name. 

Do you know what’s most important to you? While that question is difficult to answer in the perspective of life, it shouldn’t be that hard to choose a handful of apps that you can’t go through the day without. 

In Desert Island, you can select the tools inside your smartphone that are absolutely necessary (like messages, Gmail, camera, etc) while the rest of them will disappear for the next 24 hours. See how long you can stick to the limits you set yourself. Will this turn into a real challenge for you or just be an ordinary day? 

Our Verdict: the strangest wellbeing app yet.

In an attempt to answer the question of how to fight your digital addiction, Google created probably the weirdest wellbeing mobile app yet. Paper Phone suggests you ditch your smartphone altogether for a day. But not quite. 

You can pick options and tools that you’ll need throughout the day – like calendar, maps, or contacts – and then print out what’s going to be your physical paper phone for the day. It comes with instructions on how to fold it and even a credit card slot inside. 

How To Buy Inflection Ai Stock: Can You Invest In It?

2023 has witnessed an unmistakable star rise: artificial intelligence (AI) has taken center stage as the hottest tech trend. However, its influence extends beyond just industry buzz, as it has become a driving force behind substantial stock market gains. 

With many experts heralding the dawn of a new bull market, one thing remains clear: the next phase of bullish fervor is poised to propel top AI companies to soaring heights, delivering impressive returns and reaping the rewards of this AI-powered revolution.

This article delves into a comprehensive overview of Inflection AI, a company focused on crafting personalized AI solutions, as well as provides insights into its stock-related information. 

Despite Inflection AI not currently being publicly traded, the company’s recent funding round showcases notable interest from investors, hinting at potential prospects for future public investment opportunities.

Can I Buy Inflection AI Stock?

As Inflection AI is not publicly traded at the moment, it is not feasible for most individual investors to purchase Inflection AI stock directly. 

However, investors keen on the AI sector can explore opportunities in companies and funds that have invested in Inflection AI.

Some notable investors in Inflection AI include Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and NVIDIA.

For those interested in investing in the AI industry, alternative options include investing in AI-related stocks or exchange-traded funds (ETFs) that track the performance of venture capital firms. 

ETFs like the First Trust Nasdaq Emerging Growth ETF, Vanguard Growth ETF (VUG), and iShares Core Growth ETF (IWF) are examples of investment vehicles that focus on AI or emerging growth sectors.

Open AI vs. Inflection AI

In contrast, Inflection AI operates as an AI studio specializing in personalized AI solutions and human-computer interaction experiences. 

OpenAI emphasizes research and technological development, while Inflection AI aims to create practical and accessible AI experiences for individuals.

Should You Invest in Inflection AI?

Deciding whether to invest in Inflection AI requires careful consideration and analysis. Factors to assess include researching the company’s business model, growth prospects, industry trends, and competitive landscape. 

Investing in early-stage companies like Inflection AI carries inherent risks, so make an informed decision based on thorough research and your individual investment goals and risk tolerance.

Does Inflection AI have a Stock Symbol?

Inflection AI, similar to OpenAI, is not currently listed on public stock exchanges. Like OpenAI, Inflection AI is privately held and predominantly owned by its founders, investors, and employees. These individuals and entities have the opportunity to reap the benefits of Inflection AI’s growing revenues.

Since Inflection AI is not a publicly traded company, it does not have a stock symbol. As a privately held entity, Inflection AI’s ownership and shares are not available for public trading on stock exchanges.

Is Inflection a Publicly Traded Company?

Inflection AI, akin to OpenAI, is not publicly traded at present and is not listed on public stock exchanges. Inflection AI is a privately held business, similar to OpenAI, with its founders, investors, and employees holding the majority of the company’s shares. 

What Is Inflection AI?

Inflection is an AI studio that specializes in creating human-computer interaction experiences. Their flagship product, Pi, is a conversational computer program that allows users to engage in natural language conversations. The company, established in 2023, is headquartered in Palo Alto, California.

Inflection AI is driven by a mission to democratize personal AI access worldwide. As a Public Benefit Corporation, the company operates with a focus on societal benefits.

The Inflection AI team comprises esteemed AI experts with prior experience at leading organizations such as DeepMind, Google, Microsoft, OpenAI, and Meta.

According to reputable sources like Forbes and TechCrunch, Inflection AI, an AI startup dedicated to bringing personalized AI to the masses, successfully concluded a monumental funding round of $1.3 billion. 

Notable investors in the round include Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and newcomer Nvidia. With this latest funding, Inflection AI’s total raised amount reaches $1.525 billion, valuing the company at $4 billion.

Inflection AI Investors

Inflection AI has attracted investments from a range of notable individuals and companies. Some prominent investors in Inflection AI include Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and NVIDIA. 

These investors have recognized the potential of Inflection AI and have chosen to support its growth and development. While these are some of the known investors in Inflection AI, there may be additional investors who have not been publicly disclosed.

Compare Inflection AI to Competitors

Inflection AI operates within a competitive landscape alongside several other companies in the artificial intelligence (AI) industry. Let’s compare Inflection AI to some of its competitors:

1.

AI21 Labs

AI21 Labs is an AI research and development company focused on natural language processing and deep learning technologies.

While both companies operate in the AI space, Inflection AI emphasizes personalized AI solutions and human-computer interaction experiences, whereas AI21 Labs centers around language-based AI models and applications.

2.

Anthropic

Anthropic PBC is an AI startup and public-benefit corporation based in the United States. Former OpenAI members founded it, emphasizing the creation of general AI systems and language models while putting an emphasis on ethical AI practices.

As of July 2023, Anthropic has successfully secured $1.5 billion in funding.

3.

Hugging Face

Hugging Face specializes in creating tools for constructing machine learning applications. Its prominent contributions include the development of the Transformers library, designed specifically for natural language processing applications.

Additionally, Hugging Face offers a platform that facilitates the sharing of machine learning models and datasets among users.

4.

Aleph Alpha

Aleph Alpha revolutionizes human-machine interactions by researching, developing, and implementing AI-based technology across the public and private sectors.

Their focus lies in creating generative AI solutions that empower enterprises and governmental organizations to construct intelligent products.

5.

AGI Laboratory

The AGI Laboratory is dedicated to researching collective intelligence systems, e-governance, voting, and cognitive architectures, with a focus on creating infrastructure for scalable and real-time artificial general intelligence.

 While focused on personalized AI solutions, Inflection AI may have different priorities and goals compared to AGI Laboratory’s broader exploration of AGI capabilities.

6.

Irreverent Labs

Irreverent Labs, launched in 2023, focuses on developing AI tools to improve content creation for game developers and creators. Their innovative solutions, such as generating 3D images and videos from user-provided text, aim to enhance entertainment production while saving time.

 Inflection AI’s focus on personalized AI solutions and human-computer interaction sets it apart from Irreverent Labs in terms of product offerings and targeted applications.

It’s worth noting that the specific areas of expertise, product offerings, and market positioning of these companies may evolve over time, and a detailed analysis would require a comprehensive assessment of each company’s capabilities, partnerships, and market presence.

FAQs

How Much has Inflection AI Raised till now?

Inflection AI has successfully raised $1.3 billion in the most recent funding round, with significant contributions from Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, and newcomer NVIDIA. With this, the company has raised a total of $1.525 billion, valuing Inflection AI at $4 billion.

Inflection AI’s Valuation in May 2023

As of May 2023, Inflection AI had a valuation of $1.2 billion.

Who are Inflection AI’s Founders?

Inflection AI was founded in 2023 by Reid Hoffman, co-founder of LinkedIn; Mustafa Suleyman, a founding member of DeepMind; and Karén Simonyan.

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Protecting Privacy Online: How Ai Photo Anonymizer Can Help

Maintaining personal privacy has become crucial as we navigate the digital world. The constant drive to share information, opinions, and personal experiences online comes with risks, especially for those working in sensitive fields. Luckily, artificial intelligence (AI) has brought innovative solutions to protect your identity online. One such solution is the AI Photo Anonymizer from the team at Generated Photos. This free tool allows users to create synthetic images that mimic their own physical features, enabling them to stay anonymous and safe online.

The AI Anonymizer takes a clear, straight-on photo of your face and generates a synthetic image with similar features such as skin color, age, gender, hair length, etc. This generated image looks uncannily identical to you, yet completely synthetic. The result is a virtual representation that gives an idea of your appearance without revealing your true identity.

The process is straightforward. You don’t need to crop out the background or worry about multiple faces in the image. Simply upload a clear photo and let the AI do the rest.

The synthetic image produced by the Anonymizer can be used anywhere without worrying about likeness rights. It enables you to represent yourself with a generated photo that mirrors your physical characteristics. While keeping your identity anonymous, the Anonymizer gives a sense of your persona to others in the digital space.

The utility of AI-generated photos for online anonymity isn’t a new concept. Over the past year, the team at Generated Photos noticed that people, including journalists, law enforcement, and governments, frequently use their AI-generated images to protect their identities while conducting sensitive operations online.

The Anonymizer marks a significant step forward in the realm of online safety. Its user-friendly design makes it accessible for personal use, and it’s equally cost-effective for companies seeking to maintain the anonymity of their staff in the digital world.

In an era where identity protection is paramount, tools like the AI Photo Anonymizer are at the forefront of combining technology and security. By creating an environment where you can express yourself without sacrificing your privacy, the Anonymizer sets new standards for digital safety and anonymity. Give it a try and take a step toward a safer digital presence.

As we delve deeper into the digital age, the convergence of artificial intelligence and privacy tools continues to reshape the landscape of online interaction. The Anonymizer by Generated Photos exemplifies the profound impact of this union. Utilizing cutting-edge AI algorithms, it provides a dynamic solution that safeguards privacy without compromising on the need for personal representation in the digital realm.

Moreover, the Anonymizer addresses the issue of inclusivity. By generating photos that reflect the user’s skin color, age, gender, and hair length, it ensures that everyone’s identity is represented fairly and accurately. This technology makes online representation accessible to all, regardless of one’s desire to maintain anonymity.

As technology progresses, our methods of maintaining safety online must evolve. The introduction of the Anonymizer reflects the understanding of this necessity. Generated Photos is paving the way for digital safety standards. It’s an innovation that protects your privacy while allowing you to stay genuine in your online interactions.

The AI Photo Anonymizer represents a significant stride in the right direction, but privacy protection requires a comprehensive approach. Here are a few additional strategies to safeguard your privacy online.

1. Use Virtual Private Networks (VPNs)

2. Enable Two-Factor Authentication

Two-factor authentication (2FA) is a security process where users provide two different authentication factors to verify their identity. This can be something you know (like a password), something you have (like a physical token or your phone), or something you are (like your fingerprint). It offers a second line of defense if your password is compromised.

3. Practice Safe Browsing

4. Use Password Managers

A password manager is a tool that stores and manages all your passwords in an encrypted format. It allows you to use complex, unique passwords for different sites without having to remember them all. This significantly reduces the risk of your accounts being compromised.

5. Regularly Update Software and Devices

Keep your devices, software, and applications up to date. Updates often include security patches for newly discovered vulnerabilities. Delaying these updates leaves your device open to attacks.

6. Be Mindful of What You Share on Social Media

Social media platforms are a common place where oversharing can occur. Be mindful of the personal information you’re posting publicly. Make use of the privacy settings to control who can see your posts and personal details.

7. Secure Your Wi-Fi Network

Ensure that your home Wi-Fi network is secure. Use a strong, unique password and avoid using default network names. Also, consider setting up a guest network for visitors to prevent unauthorized access to your main network.

Maintaining your privacy online doesn’t stop with using AI technologies like the Photo Anonymizer. It’s an ongoing process that requires vigilance and a broad toolkit. By incorporating these methods, you can build a robust privacy shield and navigate the online world with greater confidence and peace of mind.

Preserving one’s online privacy has never been more critical in a rapidly evolving digital landscape. Innovations like the AI Anonymizer serve as powerful tools in this endeavor, enabling individuals and organizations to maintain control over their digital identities. As we continue to embrace the benefits of AI technology, we can look forward to an online world that is both inclusive and secure. 

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