Let’s start with a story. This might be my favorite story in all the annals of geekdom, which is saying something for someone whose literal job is “purveyor of geeky stories.” On March 1, 1990, in AG’s beloved hometown of Austin, Texas, the United States Secret Service raided a “suspected ring of hackers.”
It was a full-on, TV level bust: armed agents broke locks, tore up files, carted off computers, even did that “simultaneous raid so the masterminds can’t get word to their button men” thing at the home of one of the people involved. Hooray! The cops beat the bad guys! Not so much.
Right reason, wrong time
Three years and a court decision later, the Secret Service had to fess up: they’d raided a game company. A tabletop game company. As in paper and dice, neither noted for being connected to the Internet. They weren’t hackers. At all. They’d written a game about hackers, and in the grim darkness of 1990, the Secret Service was fuzzy on the difference. That poor guy who got his very own private raid? He wrote their cyberpunk setting, and had dared to do research on the subject.
That’s as close as anyone there got to l33t h4x0r doings, and it turned out to be close enough for armed cops in a private citizen’s living room without an invitation.
There’s a halfway happy ending to that story, involving money paid to the company, an epic tonguelashing from a circuit court judge, and the founding of the leading advocacy organization for digital privacy rights, but the point is the Secret Service. Their actions weren’t malicious. Stupid, yes. Hilarious in hindsight, absolutely. Catastrophic to a small business innocent of any wrongdoing, big time. But they thought they were doing the right thing. They just Did It Wrong.
Doing It Wrong
As AI saturates our lives, I reflect, as I often do, on Doing It Wrong. Fundamentally, that ridiculous case came down to a misunderstanding of context. The Secret Service didn’t have the background or expertise to differentiate between hacking and a game about hacking. That’s absurd, that’s their job, but they didn’t.
Hacking, at least most hacking, is still a bad thing.
As simultaneously hilarious and horrible as it is to pull the equivalent of yanking a guy off his couch and charging him with murder for shooting someone in “Call of Duty,” shooting people is generally undesirable outside a fictional context.
Does AI know that?
Can AI make the distinction between “die, [expletive here]” in your favorite combat simulator and “die, [expletive here]” when an unpleasant person attempts to end the pizza guy with a fork? Because the Secret Service couldn’t, and they were human. Humans are pre-built for context. Computers have to be made that way, and it’s usually really hard. That’s a shade worrisome, what with AI growing like kudzu and the data it collects being used for everything from market analysis to, yes, murder investigations.
So consider this a gentle reminder that even the smartest computer is still fundamentally a box of switches.
Zero and one, off and on, puts certain limitations on a binary system’s ability to comprehend the complex, subjective, frankly weird human condition. Getting AI to understand context is a top priority for some of the best minds in computer science, but while they’re working we h. sapiens will have to double down on patience and nuance, because one of our most pervasive tools won’t be very good at either. They may never be as good at it as we are, though three years ago I’d have said that about go.
Mind your audience
For at least the next few years, everyone from multinational corporations and national governments down to the data junkies and media consumers reading this article will need to exercise some extra caution when it comes to AI and its assessment of people and their doings.AI doesn’t understand us quite yet.It is, if not blind, at least a little nearsighted when it comes to context, which is basically the most important human thing.Click To Tweet
We’re going to have to keep doing that part ourselves. Fail in this, and you risk becoming your own hilarious Doing It Wrong cautionary tale. Nobody wants that.
This story originally ran on July 26, 2017.
Descript is a mindblowing editing shortcut for audio and video
(TECH NEWS) Descript is an automatic transcription tool that uses machine-learning to make transcribing easier.
Anyone getting into audio/video editing for the first time is almost immediately struck with the sheer enormity and complexity of it all. Even if you have the physical hardware, the proper software, and the creative spark to produce media, that doesn’t make the process of editing it all into a cohesive product any less daunting. For those of us struggling under the sisyphean weight of complicated editing workflows, a new product aims to relieve us all of this struggle. Enter Descript, an automatic transcription tool.
Descript uses machine-learning to transcribe your raw audio and video files into a dialogue script. This in itself is an incredibly valuable tool for anyone looking to transcribe podcasts, youtube videos, or whatever kind of media you produce. But this is just the beginning of what makes this app so special.
Descript is the world’s first audio word processor. Using the transcript the app creates from your audio, you can edit the text script to change the media itself. Removing the “umms” and “ahhs” from your speech — or removing whole sentences at a time — is as simple as using the backspace key on a word processor.
As a would-be podcaster, I played around with the app over the weekend, so I can tell you my initial impressions of the app. While it’s not for me (not yet, anyway), it is incredibly easy and fun and quite frankly mindblowing to use.
First things first, let’s talk about the cost.
The app works on a subscription model that pays by the minute. New users are able to upload up to 30 minutes of audio for free, but anything past that will require paying 15 cents per minute or signing up for a monthly subscription. Keep in mind these costs apply to total raw audio uploaded, not finished product audio produced. So if you’re the type (like me) to record several hours of audio per week only to trim it down to a single hour of product, this may be a bit on the wasteful side.
As for the transcription itself, the program’s machine-learning transcription transcribed my dulcet tones into the appropriate written words with nearly complete accuracy. I did have a few issues with the program understanding other speakers, but I believe that may have been a fault on my end that I’ll go into later. If the machine-learning transcription isn’t accurate enough for you, you can also choose to pay extra in order to have your audio specially transcribed by real human professionals.
The app can divide audio between different people speaking, but not automatically. If you have different audio files for each speaker, then each audio file will be labeled separately from the start. If multiple speakers are on the same audio track (like mine), then you’ll have to notate these differing speakers in the script yourself. I believe this is why the program had difficulty transcribing other speakers on the audio than myself. Being on the same audio track, the machine attuned itself to my voice (the first speaker on the recording) and was trying to interpret other people’s words as if I were the one saying them.
As for the audio editing aspect of this program, well, it really needs to be experienced to be believed. I was told what the program could do beforehand, but actually editing audio just by changing words around on a script is something else entirely. Cutting out non sequitur sentences, removing unnecessary articles, or even changing the order of words around to better suit the flow of conversation — through a literal word processor — will make you feel like an arcane grammar wizard.
Will this replace your entire audio/video workflow? Probably not. At least not yet. In addition to the cost factor which may be prohibitive to some users, there are some issues of editing that aren’t based on word choice. I found myself frustrated at my inability to change the timing of spaces between words, sometimes leaving gaps between sentences (or not enough space between words). Of course, I only had the program for a weekend, so this could very well be attributed to user error.
Whatever flaws real or imagined this program may have, it’s very important to keep in mind that Descript is the first of its kind.
It can only improve from here, not to mention potentially inspire a wave of similar programs that may very well function better. Whether or not Descript is right for you, what’s undeniable is that this program is the start of something amazing.
This eye tracking tech could be what saves VR
(TECHNOLOGY) VR has struggled with adoption rates, but this new technology could finally make it more useful in daily life.
The new HTC Vive Pro Eye VR headset made its debut at CES 2019. An updated version of the HTC Vive Pro, its features are expected to have a variety of uses over the long-term.
The Vive Pro Eye features new eye tracking technology developed in partnership with Tobii Eye Tracking. Inside the headset are sensors around the eyes to help the A.I. target what your eye is seeing. This is integrated into the UI design, allowing users to select menu options just by looking at their choice. In theory, users can choose how to interact with different A.I. characters or in VR chat spaces.
The eye tracking features Dynamic Foveated Rendering which will allow the computer to render VR objects the user is looking at to a high resolution. Likewise, images on the user’s periphery or outside the field of view will appear at a lower resolution or won’t be rendered at all. This way headset will require less performance power from its graphics card, and can still generate high-quality images in the places that matter.
Another feature is the A.I. assist where the computer can register intended targets in the VR environment based upon where your eyes are looking. This could be helpful for newcomers to VR instead of adjusting to the hand-eye coordination with the remote.
In a new industry like VR, the turnover rate for technology is fairly high, but the fovated rendering is likely to stay. Since its practicality not only enhances user experience, but also provides support from a hardware standpoint, its not outlandish to think developers will piggy-back off this new feature.
Sounds like fun? Well, currently the Vive Pro Eye is meant for business ventures rather than for consumers. But we’ll likely see this technology eventually find its way into more affordable VR products. There is no release date or price range yet available.
Google kills another of their brands – are chatbots over?
(TECH) Google sunsets another brand – does it mean *they* failed or that an entire technology failed?
Another Google invention bites the dust as we said goodbye to Allo to close out the year. Development for the Google’s instant messaging app was officially “paused” earlier in 2018, though the company says users will still have limited support.
While the reasons for Allo’s demise are as messy as they are unsurprising, the public backlash against chatbots and privacy abuse was another nail in Allo’s coffin per its definitive feature, Google Assistant.
Allo is like most messaging apps with the ability to send/receive all your favorite pictures, links, emojis, and animated cat stickers, and meant to compete with the experience of using Apple’s iMessage. The added bonus was Allo’s Google Assistant, a chatbot powered by the omnipotent Google Search engine suggesting replies and constantly “learning” as its users fed it information.
Allo could learn your favorite sports teams, nearby restaurants, or parts of your texting patterns. As if that weren’t creepy enough, users must specifically put the app into “incognito mode” in order to keep their conversations safe from potential data mining. With 2018 declaring open season on digital privacy, it’s unlikely the coming year will be any better.
The real benefits of a virtual assistant are hiding beneath a thick layer of potential data theft, legal controversies, and an unsightly image as Silicon Valley’s A.I. minions. But ultimately, Allo’s demise is connected to Google’s push to catch the trending wave of RCS communication.
Rich Communication Services (RCS) is meant to set a universal standard of communication across platforms. Currently, Allo is (was) just one messaging app among many others such as Facebook Messaging, WhatsApp, and Telegram.
Most of us are forced to jump between apps to communicate with all our contacts as service carriers/device manufactures keep us jumping through hoops.
Allo is not RCS compatible, (a.k.a. only an Allo user can message other Allo users) and its low number of users doesn’t speak well to the future. Meanwhile, RCS is a trend that’s growing in the United States and Google intends to be in the forefront getting everyone to hold hands and sing kumbaya. Can you imagine? Compatibility for all? It sounds too good to be true — are the eavesdropping chatbots coming along?
Google has always has always bid on multiple horses when coming to the various tech races.
Allo’s birth and death is no less unusual than the company deciding to switch from exclusivity to inclusivity. The path towards global connectivity will undoubtedly be littered with the bodies of other fallen platforms. Here lies Allo, right next to MySpace.
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