OpenAI, Elon Musk’s (Tesla Motors CEO) $1 billion artificial intelligence playground has turned its attention to a new project, to create their own domestic robot. It’s every homeowner’s dream come true if they can make it a reality.
A kind of test
According to the nonprofit research group behind the project, the overarching goal of creating such a robot isn’t to get humans out of doing their chores—as cool as that is—rather, they view it as a kind of test to determine whether artificial intelligence technology is progressing in the right direction. In other words, they want to make sure they can create an artificially intelligent machine that won’t try to kill us and figured they’d start by creating a robot that could do our chores for us.
Machines that do our cleaning for us are nothing new. Dishwashers, washing machines, and dryers have been doing that for years. Even ovens have a self-cleaning function these days. Then there’s the Roomba which runs around like a thing possessed keeping our floors spotless. The difference between these machines and the one OpenAI wants to create is that all of these machines we’re already using can only do one thing, and they don’t think, they merely perform the one function they were programmed to do. The robot they’re planning would be a “general purpose” robot, one that could “think” about which chores need to be done and set about doing them in the most efficient way possible, so basically Rosie from the Jetsons.
OpenAI sees this project as just one small step to creating truly intelligent machines. If it’s a success they’ll turn their attention to the bigger problems facing humanity.
Source: The Independent
Almost everyone has had that awkward experience of leaning in for a first kiss with someone. All you can do is hope that the other person was really leaning in for a kiss, and not just leaning in for a high five or something. As anyone who has ever played the dating game can attest, body language can be extremely difficult to interpret. There are thousands of little things we do with our bodies that imply so much about what we’re thinking and feeling. Now researchers at MIT are working on computer systems that can analyze and interpret body language to hopefully make that first kiss a little less awkward.
Learning through television
Our parents always yelled at us for sitting in front of the television all day because it stunted our brains. But television is how researchers at MIT are teaching their neural networks to understand body language. So far, it’s watched over 600 hours of shows like “Desperate Housewives” and “The Office” (talk about a Netflix binge).
Next, researchers gave their algorithm new videos to watch and would pass the show one second before a hug, kiss, high-five, or handshake and ask it to predict which human behavior was about to take place. Incredibly, their deep learning program predicted the correct action 43% of the time. It wasn’t as good as humans (who were correct 71% of the time) but it’s a promising step in the right direction.
Currently, MIT’s algorithm isn’t accurate enough for real world application, but we’re all waiting anxiously for the day when a device can be inconspicuously attached to us and whisper in our ear when our romantic interest is ready for that first kiss.
Source: The Motley Fool
Bill Gates recently declared artificial intelligence “the holy grail of computer science.” The industry has made massive strides in recent years and there are even more exciting things ahead. Here are ten incredible statistics about artificial intelligence:
- The AI market will grow from $420 million in 2014 to over $5 billion by the year 2020.
- By 2018, an estimated 6 billion things from appliances to cars to wearable tech will depend on AI technology.
- There are currently more than 1,000 AI start-up companies and a total of $5.4 billion has been invested into them.
- A study by an AI language company found that 80% of executives believed that AI solutions improved worker performance and created new jobs.
- Apple has Siri, Microsoft has Cortana, and Amazon has Alexis, but until recently, the majority of people were never using the personal assistants available to them. Now, only 2% of iPhone users haven’t used Siri.
- By the year 2020, 40% of all mobile interactions between users and personal assistants will be powered by data. That means that AI will enable personal assistants to make decisions for us and not just carry out requests.
- By 2020, 85% of all customer interactions with companies won’t require a human customer service representative as chatbots will be able to use artificial intelligence to solve customers’ problems.
- Over the next decade, artificial intelligence will take over 16% of all U.S. jobs, however, much of that will be offset by the fact that there will be many new jobs created to create and maintain new AI platforms and machines.
- By 2018, the fastest-growing companies will “employ” more smart machines and virtual assistants than humans.
- Artificial intelligence will be powered by GPUs rather than CPUs. Currently, Nvidia’s best GPU, the Tesla K80 is 2-5 times faster than Intel’s leading CPU, the Xeon Phi 7120.
The Dartmouth Conference of 1956 is considered by many to the be the birth of artificial intelligence. AI researches went forward from there confident that machines that could think like humans were just around the corner. That was 60 years ago; and while artificial intelligence has come a long way since then, we’re still not seeing machines that can truly think like humans do. Today researchers are once again hopeful that true artificial intelligence (an oxymoron if ever there was one) is within reach. But are we any closer than researchers were in the 50s? Here’s a look at some of the recent accomplishments, and setbacks that AI researchers are experiencing.
AI have mastered certain tasks
Where we’re seeing the biggest advancements in AI is computers that can do one thing extremely well. In the near future, we could see some jobs completely disappear as they are outsourced to machines that can do those same jobs much more efficiently and safely. We could be facing a labor displacement of a magnitude that hasn’t been seen since the industrial revolution.
Teaching AI to learn
While AI can be programmed to do certain tasks very well, a major hang up that researchers face is that they can’t teach AI to learn to do other things. All “learning” requires some kind of input from researchers. But humans could be placed in a room by themselves and can learn all on their own. This is called predictive learning or unsupervised learning and it’s an important key to solving the riddle of true artificial intelligence. For now, the big hurdle standing in the way of truly intelligent machines is the ability to teach them common sense, something humans are simply born with.
Source: Wall Street Journal
Cyber-security has come a long way in the last twenty years. In the 90s, the predominant security model used to create secure operating systems was the castle and moat approach. Everything inside the firewall was trusted and anything outside it wasn’t trusted. But emerging internet services like email meant that things needed to get through the wall. This was the beginning of the antivirus era of cyber-security, an era that we are still in. Antivirus works by identifying a threat, creating a signature, and distributing that signature so that every other computer with antivirus software installed can identify malware and defend against it.
A new era in cyber-security
Though the cyber security model hasn’t changed much since the advent of antivirus software, that could be about to change, thanks to advancements in cyber-threats. Most people creating malware use it once, and never again, which means identifying it and protecting against it in the future isn’t as helpful as it once was. A lot malware is advanced enough to slip through signature-based techniques of identifying them. Finally, the sheer volume of cyber threats continues to grow at an exponential rate and it’s getting harder to stay on top of them.
Deep learning and the future of cyber-security
Advancement in the field of deep learning allows artificial intelligence developers to create machines that can think like humans but process vast amounts of data quickly. Artificial intelligence researches are hopeful that AI may be the answer to the growing cyber threat problem. AI could theoretically identify eliminate cyber-threats as fast as they can be created.
While previous methods for protecting against cyber threats has been reactionary, the malware attacks, the antivirus software identifies it, and then makes other computers immune to it, cyber-security led by AI could take a more proactive approach in dealing with cyber threats.
There’s no denying that artificial intelligence is lightyears ahead of what it was just a few years ago. The technology continues to advance at an ever-increasing rate. But the ultimate goal of artificial intelligence researchers is to replicate human intelligence. So how do artificial intelligence and human intelligence measure up? You be the judge.
- The so-called “deep learning” that artificial intelligence is capable of isn’t really the type of profound learning like humans are capable of. Rather deep learning refers to an interconnected neural network. That means that artificial intelligence has immediate access to a wider body of knowledge, but humans are still capable of more profound thought.
- Artificial intelligence systems are able to beat the greatest chess masters in the world but they need millions of pictures (labeled by humans) to be able to learn to correctly identify a cat. Even a toddler can learn to differentiate between cats, dogs, and other animals after just a few instances of exposure to them.
- Intel’s latest processor, the i7, is one of the best CPUs that the average person can go out and buy. With four cores, it can perform four separate tasks simultaneously. But that’s no match for human biology. Even super computers are no match for the human brain’s 80 billion cells.
- The human brain can do what it does with just 10 watts of power. Artificial intelligence would need 10 terrawatts to imitate the human brain. That’s a trillion times more energy to do what the human brain is already capable of.
- Artificial intelligence runs off of algorithms programmed by humans. The algorithms haven’t actually changed much. What’s changed is the ability for artificial intelligence to run algorithms much quicker than ever before. Certain tasks, like mastering chess, depends on algorithms which is why artificial intelligence has the upper hand when it comes to playing chess.
Why even try
If after all these years, human intelligence is still vastly superior to artificial intelligence, why do artificial intelligence researchers even bother? Because despite its weaknesses when it comes to certain cognitive tasks, it can still do some things exceptionally better than humans. Artificial intelligence can sort through vast amounts of data in seconds, a task that would take humans days, weeks, or even years. Artificial intelligence is much better at humans when it comes to recognizing patterns hidden amongst large amounts of data. Artificial intelligence is far superior to humans when it comes to mathematical reasoning and computing as well.
In the end, humans need artificial intelligence. They can automate some of the more simple cognitive tasks for us such as pulling up our favorite song or performing a quick mathematical calculation. They will make our lives easier. But artificial intelligence still needs us as well. If true artificial intelligence capable of rivaling human intelligence is ever a reality, it will only be because very intelligent humans created it.
Source: Big Think