Following the viral sensation that OpenAI's ChatGPT has become, it was only a matter of time before competition arose. Now, one of the largest tech companies has introduced its own program to hopefully compete in the AI arms race. So, here's everything you need to know about Google's AI chatbot, Bard. The system functions similarly to ChatGPT but has yet to occupy the same frenetic following of the OpenAI program. Google's AI chatbot, known as Bard, is the company's answer to the recent craze in generative AI technology.

There has been a lot of amazing work done in machine learning, as well as interesting datasets released in April and May of 2020. In this article, we will go over some of the biggest AI news, research papers, and open datasets from some of the world's largest tech companies, including Microsoft, Facebook, Google, and Uber. Whether you consider yourself a data science beginner, intermediate, or expert, there is interesting information to be learned from the articles below, regardless of your skill level. From the Google AI Blog, researchers introduce Big Transfer (BiT): General Visual Representation Learning, a new approach for pre-training on image datasets at scale. The model and datasets have been open sourced and there are download links within the article.

That means communicating why an AI solution was chosen, how it was designed and developed, on what grounds it was deployed, how it's monitored and updated, and the conditions under which it may be retired. There are four specific effects of building in transparency: 1) it decreases the risk of error and misuse, 2) it distributes responsibility, 3) it enables internal and external oversight, and 4) it expresses respect for people. In 2018, one of the largest tech companies in the world premiered an AI that called restaurants and impersonated a human to make reservations. To "prove" it was human, the company trained the AI to insert "umms" and "ahhs" into its request: for instance, "When would I like the reservation? If the product team doesn't explain how to properly handle the outputs of the model, introducing AI can be counterproductive in high-stakes situations. In designing the model, the data scientists reasonably thought that erroneously marking an x-ray as negative when in fact, the x-ray does show a cancerous tumor can have very dangerous consequences and so they set a low tolerance for false negatives and, thus, a high tolerance for false positives. Had they been properly informed -- had the design decision been made transparent to the end-user -- the radiologists may have thought, I really don't see anything here and I know the AI is overly sensitive, so I'm going to move on. By being transparent from start to finish, genuine accountability can be distributed among all as they are given the knowledge they need to make responsible decisions. Consider, for instance, a financial advisor who hides the existence of some investment opportunities and emphasizes the potential upsides of others because he gets a larger commission when he sells the latter. The more general point is that AI can undermine people's autonomy -- their ability to see the options available to them and to choose among them without undue influence or manipulation. That means communicating why an AI solution was chosen, how it was designed and developed, on what grounds it was deployed, how it's monitored and updated, and the conditions under which it may be retired. There are four specific effects of building in transparency: 1) it decreases the risk of error and misuse, 2) it distributes responsibility, 3) it enables internal and external oversight, and 4) it expresses respect for people. In 2018, one of the largest tech companies in the world premiered an AI that called restaurants and impersonated a human to make reservations. To "prove" it was human, the company trained the AI to insert "umms" and "ahhs" into its request: for instance, "When would I like the reservation?

Everyone is jumping on AI and its advancements and growth in popularity in the recent years have proved a valuable opportunity for businesses and households. Big industry players have already made strides in research, and some of the largest tech companies in the world have been investing in building their own AI framework, making it accessible not only to enterprises but also independent developers. Large tech companies are harnessing the power of AI as more research developments are making strides in improvement in artificial intelligent technology. The success of its Echo products spurred Amazon to put Alexa into a wider range of devices such as lamps, speakers, clocks, and cars. Earlier in 2017, Amazon launched a smart Wi-Fi speaker that uses voice recognition to not only respond to commands, but also display what it sees.

Artificial Intelligence is already improving and automating many everyday tasks. And while computers can't replace humans quite yet, they're doing a great job of taking care of the mundane tasks we don't want to do.

From artificial intelligence (AI) that can recognize faces, choose music for you based on your mood, and even drive your car, the technology has come a long way in recent years. Although the concept of intelligent machines has been around since ancient history as part of Greek mythology, only in recent decades has the scientific community made significant advances in practical uses of AI. Consumer applications for AI only took off in the past few years, with the introduction of Amazon's Alexa, the AI that resides in the handy little Bluetooth speaker, Echo. The business world, too, is just starting to explore AI's possible applications in big data analysis for customer relationship management, marketing, and more. Most of the world's tech giants are taking note, exemplified through both internal investments in AI research and development and the acquisition of AI startups.

From artificial intelligence (AI) that can recognize faces, choose music for you based on your mood, and even drive your car, the technology has come a long way in recent years. Although the concept of intelligent machines has been around since ancient history as part of Greek mythology, only in recent decades has the scientific community made significant advances in practical uses of AI. Consumer applications for AI only took off in the past few years, with the introduction of Amazon's Alexa, the AI that resides in the handy little Bluetooth speaker, Echo. The business world, too, is just starting to explore AI's possible applications in big data analysis for customer relationship management, marketing, and more. Most of the world's tech giants are taking note, exemplified through both internal investments in AI research and development and the acquisition of AI startups.