We introduce EvalAI, an open source platform for evaluating and comparing machine learning (ML) and artificial intelligence algorithms (AI) at scale. EvalAI is built to provide a scalable solution to the research community to fulfill the critical need of evaluating machine learning models and agents acting in an environment against annotations or with a human-in-the-loop. This will help researchers, students, and data scientists to create, collaborate, and participate in AI challenges organized around the globe. By simplifying and standardizing the process of benchmarking these models, EvalAI seeks to lower the barrier to entry for participating in the global scientific effort to push the frontiers of machine learning and artificial intelligence, thereby increasing the rate of measurable progress in this domain. Our code is available here.

As the recently launched AI Monthly digest shows, significant improvements, breakthroughs and game-changers in machine learning and AI are months or even weeks away, not years. It is, therefore, worth the challenge to summarize and show the most significant AI trends that are likely to unfold in 2019, as machine learning technology becomes one of the most prominent driving forces in both business and society. According to a recent Deloitte study, 82% of companies that have already invested in AI have gained a financial return on their investment. For companies among all industries, the median return on investment from cognitive technologies is 17%. AI is transforming daily life and business operations in a way seen during previous industrial revolutions.

Google has moved the latest version of its Chrome OS from beta to release status, and with the arrival of version 72 there are changes you'll notice -- if you're using the right kind of device. One of the biggest adjustments is its native integration of Google Assistant (and Android 9 Pie) that brings it to more Chromebooks. Similar to Android, there's a pill-shaped bar at the center of the screen that can expand for users to type into, or access via voice controls. If you're using Chrome OS on some convertible tablet-style hardware like the Pixel Slate, you'll probably appreciate updates to the Chrome browser that make it easier to control with the touchscreen while in tablet mode. On the security front, Chrome OS 72 sandboxes its "Shill" network manager to prevent exploits like this one uncovered in 2016, and it delivers the USBGuard feature that secures down access to its ports when the device is locked.

For the next seven weeks, anyone who's inclined can go to 205 Hudson Street in New York City and take over someone else's apartment. Smart devices like the kettles, lighting and speakers of four homes connect directly to laptops in the corner of an art gallery. Cameras are trained on bathrooms, kitchens and living areas. Visitors can sit down and become a human Alexa, playing music, eavesdropping on conversations through microphones and communicating with the inhabitants via text-to-speech. Each home -- three in Brooklyn, one in San Francisco -- will be "live" for two hours a day.

Apple could be planning to introduce an emojii version of its Siri virtual assistant, according to a new patent application from the tech giant. The patent request, filed with the US Patent and Trademark Office, describes an emoji-based avatar for a smart home speaker that can adapt to a user's mood. Though not mentioned by name in the patent, the description of the smart speaker accurately resembles that of the Apple HomePod. Apple's patent application describes a "humanistic avatar, a simplified graphical representation of a digital assistant such as an emoji-based avatar" – essentially a cartoon version of Siri. Depending on what request is made through the smart speaker, the emoji assistant would be able to react appropriately.

The workplace chatbots are coming! The workplace chatbots are coming! And in a few years, there will be even more. According to Gartner, by 2021 the daily use of virtual assistants in the workplace will climb to 25 percent. That will be up from less than 2 percent this year.

When I reviewed First Alert's Onelink Safe & Sound smoke alarm in mid-2018, I found it to be a powerful entry in the smart smoke detector market. Its inclusion of Bluetooth and an Amazon Echo-compatible smart speaker set it apart from every smoke and carbon-monoxide detector on the market. But its $199 price tag also made it far and away the most expensive device of its type on the market--and that price hasn't budged since its release. Enter the Onelink Smoke Carbon Monoxide Alarm, which lowers the cost of the original product by stripping out its most compelling features: The smart speaker and Bluetooth. Like other products in this category, the Onelink Smoke Carbon Monoxide Alarm is designed to extend the capabilities of a smoke detector by linking it with your smartphone. It still functions by firing off a (rather loud) local siren whenever smoke or CO are detected, but it also (supposedly) sends push alerts to your mobile device, a feature that is most helpful for times when you aren't at home but still want the peace of mind that it's not on fire.

AI for business is an incredibly helpful tool for enterprises when used correctly. Just take a look at some numbers recently published in a Forbes Magazine article: 38% of 235 enterprises the NBRI looked at are already using AI for a variety of tasks; and more importantly, 62% of these enterprises expect to be using AI by 2018. But here's the rub: AI is a massively broad catch all term. Over the last few years, people have termed all sorts of machine coding techniques as'AI;' in fact, saying that your business uses AI is kind of like saying your garden has plants. In other words, AI is an umbrella for a whole host of technologies.

This is that Latent semantic analysis (LSA) do. It is based on how frequent you see the word on the exact topic. Like, there are more tech terms in tech articles, for sure. The names of politicians are mostly found in political news, etc. Yes, we can just make clusters from all the words at the articles, but we will lose all the important connections (for example the same meaning of battery and accumulator in different documents). LSA will handle it properly, that's why its called "latent semantic". So we need to connect the words and documents into one feature to keep these latent connections.

Rapid innovation and productivity breakthroughs require an accelerated digital transformation strategy that melds people, business processes, advanced analytics, and new human/machine interaction technologies. Today, it is the supervised machine learning segment of AI that is generating the most economic value. But as digital transformation accelerates, the abundance of data that AI can consume will drive the speed of AI adoption even faster, including its unsupervised learning segment. We need only look at how quickly conversational AI (CAI) has become part of our everyday lives as we query Alexa, Siri or Cortana. But in the enterprise the interactions can be extremely complex, such as "Hey CAI, summarize the minutes and action items from the recording of the last board meeting."