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Mars rover Perseverance has landed on the surface of Mars after a white-knuckle descent involving picking a landing spot just moments before making a rocket-powered sky crane landing. The rover immediately sent back its first image of Jezero crater, which it will be exploring over the course of its mission.
A clearly tense but optimistic team watched as Perseverance made its final approach to Mars a few hours ago, confirming it was on track to hit the bullseye of Jezero Crater, the ancient delta where the rover will soon be roving.
Except for a few brief but expected communications blackouts caused by the superheated air around the craft as it entered the thin Martian atmosphere, the lander sent back a continuous stream of updates to the team on Earth — considerably delayed, of course, by the distance to the other planet.
The team, and charmingly the on-screen hosts at mission HQ audibly gasped, whispered “yes!” and made other signs of their excitement as news trickled in that atmosphere entry had occurred on time, that the craft hadn’t broken up during the ten-G braking maneuver, that the parachute had deployed, that a landing site was found by the ground-facing radar, that the powered descent and sky crane had commenced, and at last finally that the rover had safely touched down on the surface.
Image Credits: NASA
Cheering but, in accordance with COVID-19 precautions not (as they normally would) hugging each other, the team celebrated the landing and soon were treated to the first images sent back from the rover.
These initial pictures are low-quality ones sent just seconds after landing by the “hazard camera,” a fisheye used for navigation. As the dust settles (literally) and the rover initiates its more powerful devices and cameras, we’ll have new, color images — probably within an hour or two.
For a more complete look at the mission and its remarkable landing method, you can read yesterday’s profile of the Perseverance mission. The next few days will probably be less exciting than the terror-inducing landing, but soon the rover will be up and running around Jezero, looking for evidence of life on Mars and testing technology that could be used by human visitors in the future.
“We’re not ready to go there with astronauts yet, but the robots are ready,” said JPL director Michael Watkins on the broadcast. “We start by sending, you know, our eyes and arms there in the form of a robot. It is just fantastic to be able to do that, and to learn from each rover, learn from the science and the engineering, and make the next one better, and make more and more discoveries. Every time we do one of these missions, we make fabulous discoveries — and you know, each one is more exciting than the last.”
Image Credits: NASA/JPL-Caltech
The exciting thing everyone is looking forward to, Mars helicopter Ingenuity, will hopefully take flight soon as well.
“We have a series of major milestones between now and the first flight. Tomorrow, we’ll turn on the helicopter, and the space station could confirm its health. The next major milestone will be when the rover deploys the helicopter on the surface, and that marks the first moment that Ingenuity operates on its own in a standalone manner, said MiMi Aung, project manager and engineering lead for Ingenuity. “Surviving that first cold frigid night of Mars will be a major milestone, then we’ll execute a series of checkouts, and then we will perform that very important first flight. And if the first flight is successful, we have up to four more flights in the thirty Martian days that we have set aside for our flight experiments.”
The helicopter project will definitely be novel, but it’s not just about recording a first for the sake of NASA being able to say they did it; Ingenuity will hopefully lay a firm technical foundation for future exploration.
“A helicopter flying far ahead of rovers and astronauts in the future can provide high=definition reconnaissance information for the rovers and the astronauts before they take long journeys,” Aung said. “And as importantly, being able to fly will enable us to get to places that we cannot get to with rovers and astronauts, like sides of steep cliffs, deep inside crevices, all areas of high scientific interest. It will be game changing.”
Artificial intelligence and machine-learning technologies have evolved a lot over the past decade and have been useful to many people and businesses, especially in the realm of finance, banking, investment and trading.
In these industries, there are many activities that machines can perform better and faster than humans, such as calculations and financial reporting, as long as the machines are given the complete data.
The AI tools being built by humans today are becoming another level more robust in their ability to predict trends, provide complex analysis, and execute automations faster and cheaper than humans. However, there has not been an AI-powered machine built yet that can trade on its own.
There are many activities that machines can perform better and faster than humans, such as calculations and financial reporting, as long as the machines are given the complete data.
Even if it was possible to train such a system that could replace human judgment, there would still be a margin of error, as well as some things that are only understandable by human beings. Humans are still ultimately responsible for the design of AI-based prediction machines, and progress can only happen with their input.
Data is the backbone of any prediction machine
Building an AI-based prediction machine initially requires an understanding of the problem being solved and the requirements of the user. After that, it’s important to select the machine-learning technique that will be implemented, based on what the machine will do.
There are three techniques: supervised learning (learning from examples), unsupervised learning (learning to identify common patterns), and reinforcement learning (learning based on the concept of gamification).
After the technique is identified, it’s time to implement a machine-learning model. For “time series forecasting” — which involves making predictions about the future — long short-term memory (LSTM) with sequence to sequence (Seq2Seq) models can be used.
LSTM networks are especially suited to making predictions based on a series of data points indexed in time order. Even simple convolutional neural networks, applicable to image and video recognition, or recurrent neural networks, applicable to handwriting and speech recognition, can be used.
Source: https://techcrunch.com/2021/02/18/creating-a-prediction-machine-for-the-financial-markets/
Uber today notified employees that it will extend its work from home policy through September 13.
“In considering the extension, we took into account the latest scientific data and experts’ views; the fact that different countries are at different stages of recovery; and the start of the school year,” Uber Chief People Officer Nikki Krish wrote in an email, viewed by TechCrunch, to employees. “[…] We know that some CommOps, IT, or other roles require physical presence in an office, so please continue to work within the policies your teams have developed—however, as always, we won’t force anyone to go into the office if they have medical concerns.”
Uber is also encouraging employees to get vaccinated when it’s possible to do so. In the email, Krish said Uber employees will be able to take time off in order to get vaccinated.
In August, Uber notified employees that they should expect to work from home through June 2021. As for other tech companies, Google in July extended its work from home policy through the end of June 2021, while Facebook in August extended its remote work policy until July 2021.
Post-COVID, Uber will likely have a hybrid work model, Krish said, but it’s still a work in progress.
“We’re taking a number of aspects into consideration, such as how being physically together benefits or reduces productivity, collaboration, and engagement,” she wrote. “We’ll update you on where things stand in a few weeks, and along the way as we make progress.”
Source: https://techcrunch.com/2021/02/18/uber-extends-work-from-home-policy-through-mid-september/
If you use Office, Microsoft would really, really, really like you to buy a cloud-enabled subscription to Microsoft 365 (formerly Office 365). But as the company promised, it will continue to make a stand-alone, perpetual license for Office available for the foreseeable future. A while back, it launched Office 2019, which includes the standard suite of Office tools, but is frozen in time and without the benefit of the regular feature updates and cloud-based tools that come with the subscription offering.
Today, Microsoft is announcing what is now called the Microsoft Office LTSC (Long Term Servicing Channel). It’ll be available as a commercial preview in April and will be available on both Mac and Windows, in both 32-bit and 64-bit versions.
And like with the previous version, it’s clear that Microsoft would really prefer if you just moved to the cloud already. But it also knows that not everybody can do that, so it now calls this version with its perpetual license that you pay for once and then use for as long as you want to (or have compatible hardware) a “specialty product for specific scenarios. Those scenarios, Microsoft agrees, include situations where you have a regulated device that can’t accept feature updates for years at a time, process control devices on a manufacturing floor and other devices that simply can’t be connected to the internet.
“We expect that most customers who use Office LTSC won’t do it across their entire organization, but only in specific scenarios,” Microsoft’s CVP for Microsoft 365, Jared Spataro, writes in today’s announcement.
Because it’s a specialty product, Microsoft will also raise the price for Office Professional Plus, Office Standard, and the individual Office apps by up to 10%.
“To fuel the work of the future, we need the power of the cloud,” writes Spataro. “The cloud is where we invest, where we innovate, where we discover the solutions that help our customers empower everyone in their organization – even as we all adjust to a new world of work. But we also acknowledge that some of our customers need to enable a limited set of locked-in-time scenarios, and these updates reflect our commitment to helping them meet this need.”
If you have one of these special use cases, the price increase will not likely deter you and you’ll likely be happy to hear that Microsoft is committing to another release in this long-term channel in the future, too.
As for the new features in this release, Spataro notes that will have dark mode support, new capabilities like Dynamic Arrays and XLOOKUP in Excel, and performance improvements across the board. One other change worth calling out is that it will not ship with Skype for Business but the Microsoft Teams app (though you can still download Skype for Business if you need it).
Source: https://techcrunch.com/2021/02/18/microsoft-announces-the-next-perpetual-release-of-office/
Photomath, the popular mobile app that helps you solve equations, has raised a $23 million Series B funding round led by Menlo Ventures. The app is a massive consumer success, and chances are you might already know about it if you have a teenager in your household.
The app lets you point your phone’s camera at a math problem. It recognizes what’s written and gives you a step-by-step explanation to solve the problem. You might think that it’s the perfect app for lazy students.
But there are many different use cases for Photomath. For instance, you can write an equation in your notebook and use Photomath to draw a graph.
Typing an equation on a keyboard is quite difficult. That’s why bridging the gap between the physical world and your smartphone is key to Photomath’s success. You can just grab a pen and write something down on a piece of paper. Essentially, it’s an AR calculator.
GSV Ventures, Learn Capital, Cherubic Ventures and Goodwater Capital are also participating in today’s funding round.
Behind the app’s success, there’s an interesting story. Photomath was originally designed as a demo app for another company called MicroBlink. At the time, the team was working on text recognition technology. It planned to sell its core technology to other companies that might find it useful.
In 2014, they pitched MicroBlink at TechCrunch Disrupt in London. And things changed drastically overnight as Photomath reached the first spot of the iOS App Store.
Photomath has now attracted over 220 million downloads. As of this writing, it is still #59 in the U.S. App Store, one rank above Tinder. Other companies tried to build competitors, but it seems like they didn’t manage to crush the tiny European startup.
The app seems even more relevant as many kids are spending more time studying at home. They can’t simply raise their hand to call the teacher for some help.
Photomath is free and users can optionally pay for Photomath Plus, a premium version with more features, such as dynamic illustrations and animated tutorials.
