- Fake News Is Rampant, Here Is How Artificial Intelligence Can Help
Artificial intelligence (AI) is now on the job to combat the spread of misinformation on the internet and social platforms thanks to the efforts of start-ups such as Logically. While AI is able to analyze the enormous amounts of info generated daily on a scale that’s impossible for humans, ultimately, humans need to be part of the process of fact-checking to ensure credibility. As Lyric Jain, founder and CEO of Logically, said, toxic news travels faster than the truth. Our world desperately needs a way to discern truth from fiction in our news and public, political and economic discussions, and artificial intelligence will help us do that.
2. Why is Artificial Intelligence so Energy Hungry?
Neural network is a powerful type of machine learning which models itself by mirroring the human brain. Composed of node layers, a neural network attempts to recognize the underlying relationships in a data set by mimicking human brain functions. Each node is connected with another and has an associated weight and threshold. Suppose the output value of a node is higher than the specified threshold value, it implies that the node is activated and ready to relay data to the next layer of the neural network.
The advancements in artificial intelligence have been possible thanks to the powerful GPU (Graphical Process Units) we have today. These GPUs generally consume a lot of electricity. According to NVIDIA, the maximum power dissipated by a GPU equals 250 W, which is 2.5 times higher than that of the Intel CPU. Meanwhile, researchers believe that having larger artificial intelligence models can lead to better accuracy and performance. This is similar to the performance of gaming laptops, which though have high capabilities than a regular laptop but also gets heated up more quickly due to heavy performance. Today, one can rent online servers with dozens of CPUs and strong GPUs for few minutes and quickly develop powerful artificial intelligence models.
As per OpenAI, a San Francisco-based AI research lab, since the early years of machine learning development to 2012, the number of computational resources required by the technology doubled every two years (drawing parallels with Moore’s law of growth in processor power). However, after 2012, the trajectory of computing power for building top-notch models, on average has doubled every 3.4 months. This means that the new computational requirements translate to negative environmental impacts due to artificial intelligence. Also now experts argue that building massive artificial intelligence models does not necessarily mean better ROI in terms of performance and accuracy. So companies may have to make trade-offs between accuracy and computational efficiency.
3. Makers of Sophia the robot plan mass rollout amid pandemic
“Social robots like me can take care of the sick or elderly,” Sophia says as she conducts a tour of her lab in Hong Kong. “I can help communicate, give therapy and provide social stimulation, even in difficult situations.”
Since being unveiled in 2016, Sophia – a humanoid robot – has gone viral. Now the company behind her has a new vision: to mass-produce robots by the end of the year.
Hanson Robotics, based in Hong Kong, said four models, including Sophia, would start rolling out of factories in the first half of 2021, just as researchers predict the pandemic will open new opportunities for the robotics industry.
“The world of COVID-19 is going to need more and more automation to keep people safe,” founder and chief executive David Hanson said, standing surrounded by robot heads in his lab.
Hanson believes robotic solutions to the pandemic are not limited to healthcare, but could assist customers in industries such as retail and airlines too.
20-Jan-2021 By Katy Askew
COVID-19 has accelerated interest in the role that automation, robotics and data can play in food and agricultural production. We speak to industry leaders to learn about the latest developments.