For the most part, Zoom has dominated video conferencing, but it might soon face competition thanks to NVIDIA. Recently, NVIDIA announced its new GPU-Accelerated AI Platform, NVIDIA Maxine, that it says will “vastly improve streaming quality” and offer incredible AI-powered features.
NVIDIA Maxine is a cloud-native video-streaming AI platform so data doesn’t need to be processed on local servers. Instead, NVIDIA’s servers process the information so users can use the cool AI features without having to purchase any new specialized hardware.
“NVIDIA Maxine integrates our most advanced video, audio, and conversational AI capabilities to bring breakthrough efficiency and new capabilities to the platforms that are keeping us all connected,” said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA, in a press release.
Maxine’s “breakthrough efficiency” can be seen in its AI-based video compression technology. The AI tech reduces the bandwidth used on a call to one-tenth of the H.264 video compression standard without compromising video quality. In doing so, less data is transmitted back and forth so slow internet connection and limited bandwidth won’t be a problem anymore. Hopefully, this helps bring an end to the dreaded “you have a poor connection, blah, blah, blah” message.
Some of the features that make NVIDIA Maxine standout are face alignment and gaze correction. These two features allow for a better face-to-face conversation. For instance, people will no longer appear to be staring off into outer space. With face alignment, the software will automatically adjust people so it looks like they are facing each other. And, with gaze correction, it will help simulate eye contact. According to NVIDIA, “These features help people stay engaged in the conversation rather than looking at their camera.”
Also, if developers choose to do so, they can allow users to choose an animated avatar. These avatars offer a realistic feel because they are driven by a person’s “voice and emotional tone in real-time.” Plus, the auto frame feature automatically follows the person in the frame so they are always in view. This is great when you’re doing a presentation or demo.
The feature that stands out to me is the noise cancellation filter that removes background noise. Anyone with a toddler or dog will be a big fan of that one! Continually pressing the mute and unmute button could finally become a thing of the past.
Maxine also has a “conversational AI”. With NVIDIA Jarvis (not to be confused with Iron Man’s Just A Rather Very Intelligent System), developers can integrate virtual assistants to take notes, set action items, and answer questions in human-like voices. Additionally, this AI offers translations and closed captions all in real-time.
By taking a look at what NVIDIA Maxine has to offer, there is no denying Zoom has a lot of work to do if it wants to stay on top. Although it did dabble with real-time captioning back in June, Zoom’s offering was very limited. And, Maxine is on its way up.
Early access to the NVIDIA Maxine platform is available to Computer vision AI developers, software partners, startups, and computer manufacturers creating audio and video apps and services.
3 cool ways bug-sized robots are changing the world
(TECH NEWS) Robots are at the forefront of tech advancements. But why should we care? Here are some noticeable ways robots are changing the world.
When we envision the robots that will (and already are) transforming our world, we’re most likely thinking of something human- or dog-sized. So why are scientists hyper-focusing on developing bug-sized (or even smaller!) robots?
Tiny robots could assist in better drug delivery, as well as conduct minor internal surgeries that wouldn’t otherwise require incisions.
We’ve all heard about the robot dogs that can rescue people who’ve been buried beneath rubble or sheets of snow. However, in some circumstances these machines are too bulky to do the job safely. Bug-sized robots are a less invasive savior in high-intensity environments, such as mine fields, that larger robots would not be able to navigate without causing disruption.
Much like the insects after which these robots were designed, they can be programmed to work together (think: ants building a bridge using their own bodies). This could be key in exploring surfaces like Mars, which are not safe for humans to explore freely. Additionally, tiny robots that can be set to construct and then deconstruct themselves could help astronauts in landings and other endeavors in space.
Well, perhaps the most important reason is that insects have “nature’s optimized design”. They can jump vast distances (fleas), hold items ten times the weight of their own bodies (ants) and perform tasks with the highest efficiency (bees) – all qualities that, if utilized correctly, would be extremely beneficial to humans. Furthermore, a bug-sized bot is economical. If one short-circuits or gets lost, it won’t totally break the bank.
Something scientists have yet to replicate in robotics is the material elements that make insects so unique and powerful, such as tiny claws or sticky pads. What if a robot could produce excrement that could build something, the way bees do in their hives, or spiders do with their webs? While replicating these materials is often difficult and costly, it is undoubtedly the next frontier in bug-inspired robotics – and it will likely open doors for humans that we never imaged possible.
This is all to say that in the pursuit of creating strong, powerful robots, they need not always be big in stature – sometimes, the tiniest robots are just the best for the task.
4 ways startups prove their investment in upcoming technology trends
(TECH NEWS) Want to see into the future? Just take a look at what technology the tech field is exploring and investing in today — that’s the stuff that will make up the world of tomorrow.
Big companies scout like for small ones that have proven ideas and prototypes, rather than take the initial risk on themselves. So startups have to stay ahead of technology by their very nature, in order to be stand-out candidates when selling their ideas to investors.
Innovation Leader, in partnership with KPMG LLP, recently conducted a study that sheds light onto the bleeding edge of tech: The technologies that the biggest companies are most interested in building right now.
The study asked its respondents to group 16 technologies into four categorical buckets, which Innovation Leader CEO Scott Kirsner refers to as “commitment level.”
The highest commitment level, “in-market or accelerating investment,” basically means that technology is already mainstream. For optimum tech-clairvoyance, keep your eyes on the technologies which land in the middle of the ranking.
“Investing or piloting” represents the second-highest commitment level – that means they have offerings that are approaching market-readiness.
The standout in this category is Advanced Analytics. That’s a pretty vague title, but it generally refers to the automated interpretation and prediction on data sets, and has overlap with Machine learning.
Wearables, on the other hand, are self explanatory. From smart watches to location trackers for children, these devices often pick up on input from the body, such heart rate.
The “Internet of Things” is finding new and improved ways to embed sensor and network capabilities into objects within the home, the workplace, and the world at large. (Hopefully that doesn’t mean anyone’s out there trying to reinvent Juicero, though.)
Collaboration tools and cloud computing also land on this list. That’s no shock, given the continuous pandemic.
The next tier is “learning and exploring”— that represents lower commitment, but a high level of curiosity. These technologies will take a longer time to become common, but only because they have an abundance of unexplored potential.
Blockchain was the highest ranked under this category. Not surprising, considering it’s the OG of making people go “wait, what?”
Augmented & virtual reality has been hyped up particularly hard recently and is in high demand (again, due to the pandemic forcing us to seek new ways to interact without human contact.)
And notably, AI & machine learning appears on rankings for both second and third commitment levels, indicating it’s possibly in transition between these categories.
The lowest level is “not exploring or investing,” which represents little to no interest.
Quantum computing is the standout selection for this category of technology. But there’s reason to believe that it, too, is just waiting for the right breakthroughs to happen.
Will AI take over copywriting roles? This tool hopes to make that a reality
(TECH NEWS) CopyAI hopes to give copywriters a run for their… well, WPM. But how much can AI fully replace copywriting skills?
Copywriting is an important trade. Writers are often able to breathe life into otherwise formulaic websites peddling products which, sans the copy from those writers, might very well suffer a fate of relative obscurity. However, copywriters are also expensive, and their duties—indispensable as they may be—can be replicated fairly easily by little more than basic machine learning.
The question is this: Can AI replace copywriters? That’s a question that CopyAI hopes to answer with a resounding “yes”.
CopyAI is an “AI powered [sic] assistant for writing and brainstorming marketing copy.” This makes it a powerful tool to complement human writing, at the very least; is it enough to put people like me out of a job?
From my experience with the tool, no—at least, not yet. CopyAI can’t create an engagement strategy, respond to customers, spin testimonials to evoke heart-felt reactions, or analyze its own trends.
But that doesn’t detract from how freaking cool it is in practice.
CopyAI asks for very little from its user. Upon selecting a style of copy—Facebook Market, website carousel, or even page header, for example–you are prompted to enter the title of your product and a couple of short sentences describing it in the context of your ad. CopyAI does the rest, and while the results can be hilariously out of touch, you’re able to pick the ones that sound the most like your desired copy and then generate more options that sound similar.
The service has a huge number of different options for advertisement types, and you can use multiple different copy projects in one specific campaign.
Naturally, CopyAI has a few flaws, most of which replicate the problems we’ve seen with machine learning-based writing in the past: It doesn’t sound quite human enough to be comfortable. However, that’s a problem for a skilled copywriter to solve—and quickly, thus making something like CopyAI a potentially preferable choice for mass copywriting.
So, again, we ask: Is there a way for CopyAI to replace copywriters entirely in the future? Probably not. The copy it produces is intriguing, and often close enough that underfunded campaigns might find some value in using it short-term, but it doesn’t have the punch that a real person can pack into an advertisement.
That said, combining CopyAI with a small team of copywriters to reduce burnout—and repetition—could make for some very efficient work on the back end.
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