Since OpenAI has not open-sourced the code for ChatGPT, replicating the chatbot is a herculean task, and even the big-tech are struggling. But, AI startup Colossal-AI has found a way to build your own ChatGPT with less computing resources. Towards this goal, the company has leveraged a PyTorch-based implementation that covers all three stages from pre-training, reward model training, and reinforcement learning. They offer a demo version of the training process that requires only 1.62 GB of GPU memory and can be done on a single consumer-grade GPU, with 10.3x growth on one GPU model capacity. Check out the GitHub repository here.

The vast list of artificial intelligence applications continually increases as researchers, technologists, and scientists try to leverage computing power to gain competitive edges over the more slowly adopting set. Today I want to traipse across the American business and tech landscape and present a few of the new and hopefully intriguing upgrades of these mostly familiar devices and services being brought into the 21st century via AI. First a quick overview of the concept of AI and where it's come from over the past years and decades. Earlier writings comingled two phrases to identify the technology: artificial intelligence, which has become the well-known marketable way to talk about the tech, and "computational intelligence," which might be useful amongst a group of AI--err, CI?--subject matter experts, but doesn't carry the cachet of its more widely accepted phrase. For anyone who uses either phrase, it's generally understood to refer to some sort of machine-based intelligence.

With more organizations and professionals relying on remote working technologies, there has been an increase in cybercrime during the global pandemic. Understandably, CIOs and CTOs have concerns when it comes to cybersecurity, their two biggest challenges being workers using their own devices at work (37%) and securing the Internet of Things (35%). However, just 34% of respondents said they were capable of tracking and managing between 26-50% of the connected devices used in their organizations, and just 20% said they could do this for 51-75% of IoT devices. Elsewhere in the survey, CIOs and CTOs provided a glimpse into their biggest priorities since the outbreak of coronavirus at the start of 2020. It found that IT leaders are quickly adopting cloud computing (55%), 5G (52%), as well as AI and machine learning (51%) in response to the pandemic.

Give us your feedback Thank you for your feedback. Whether you leave business school to become a corporate manager, a professional high performer or an entrepreneur, you will spend much of your time on tasks unrelated to your expertise. Only the most senior executives now have dedicated personal assistants and so the more mundane work of email, scheduling meetings and booking travel eats up your time. A new generation of employees is looking for ways to reclaim that time so they can spend it finding solutions to serious problems: the work that will get them credit and help them advance. This work also develops their expertise and helps them remain valuable when artificial intelligence finally becomes clever enough to do all the most predictable tasks.

With Apple deciding to use new Depth Sensing technology for the iPhone X's Face ID, many believe that Android phone makers might start using it for their own devices. However, it looks like many Android flagships coming out during the first half of 2018 won't have the same 3D-sensing feature. Industry sources say that smartphone vendors, particularly in China, are actually more interested in selling the rest of their unsold inventories. This is also the reason why many of those Android phone manufacturers are postponing plans to develop new technologies like fast charging, wireless charging and Face ID-like features, according to Digitimes. Another reason that's hindering the adoption of 3D-sensing cameras on Android smartphones is the slow yield rates for producing components.

So-called connected homes, which feature a network of devices and appliances that communicate with each other and can be remotely monitored and controlled, are becoming increasingly popular and affordable. By 2020, the connected home market could be worth nearly 150 billion globally, according to professional services firm PricewaterhouseCoopers. Most Americans surveyed by the company said that within the next decade, using a single remote to control everything in the home will be the norm. "Younger generations view these devices as adding to the livability of the home," said Mark Lesswing, chief technology officer for the National Assn. of Realtors trade group. "They're early adopters now, but in three years, I think this becomes the norm."

It was a bit surprising, on Tuesday morning, to see Google's C.E.O., Sundar Pichai, stride onstage in San Francisco's Ghirardelli Square and start talking about the quality of Google's software and the information it brings to people. The event had been billed as a presentation of new hardware devices; some were even describing it as the most significant event of its kind that Google had ever held. And yet, there was Pichai, going on about how Google's software allows people to connect with "over seventy billion facts about people, places, and things." Only at the end of this speech did he get to a hardware-related point: all this impressive software would be embedded in Google's new devices. Google is in the middle of an awkward transition.

Whether you read past the first line in this article or not is your choice, but inside your skull this decision will be accompanied by a buzz of activity in your neurons. But trying to pin down something as intangible as free will to a region of the brain is tricky, with most studies showing response to commands, rather than a choice made by someone's own volition. Now a team of neuroscientists in the US claim to have caught the brain in the act, capturing the activity right at the point it makes a decision – effectively pinpointing free will in the brain. Using functional MRI scans, researchers were able to show which regions showed a surge in activity which caused a boost of oxygen rich blood to the regions. Using functional MRI scans, scientists showed which brain regions had a surge in activity before a free decision is made.