clarkam harben herris
Cristoforo Kanoy
Question: if this continues unfixed by Roku (I guess it's still the thinking that issue arises with Roku Stream bars on YouTube TV), is it accurate to believe one could buy a Roku Ultra (for instance) and not have these problems? Alternatives? Or, have Roku send us a new Ultra or other model that works! Thanks to all those working to provide Roku with info they need, to come up with a 'software update' that'll fix this! donald4972
My soundbar Model:9102X also freezes when trying to fast forward NBA games on YouTubeTV.com. Doesn't happen every time, but many times before the game is over. It used to be that I could reboot my soundbar and it would continue with the program. That DOESN'T work now. Once it happens, rebooting the soundbar, pulling the power cord for several minutes, Nothing helps. It also freezes quite often if I am trying to watch key plays. Mine also freezes if I am watching Netflix as well, again sometimes if I try to fast forward through commercials. Always on recorded programs. I have a ROKU 3, two ultra's and none of them freeze like this soundbar. I really believe the problem is in the ROKU soundbar, not routers Youtube, netflix, etc. IT really sucks... This problem with the soundbars should and could be fixed, because the other players do not have the problem. Perhaps buying another brand of soundbar as was suggested by one respondent would resolve the problem? I would just go back to the ultra, but the sound from my TV is really bad, and that is the reason I bought this soundbar in the first place. Like I said I really believe the problem is just a fault with these soundbars.
Skip backward or forward 10 seconds: Press left or right on the clickpad ring (Siri Remote 2nd generation or later) or rest your finger on the touch surface, then press left or right (Siri Remote 1st generation). Press again to skip another 10 seconds.
Continuously rewind or fast-forward: Press and hold left or right on the clickpad ring (Siri Remote 2nd generation or later) or touch surface (Siri Remote 1st generation). Press left or right repeatedly to cycle through rewind or fast-forward speed options (2x, 3x, 4x). Press the clickpad center or the Play/Pause button to resume playback.
Siri Remote (2nd generation or later): Press down on the clickpad ring to go directly to the Info tab, or rest your finger on the clickpad to show playback controls, then swipe down to show the Info and Up Next tabs.
Swap audio from the larger to the smaller picture: Press the TV button on the Siri Remote. To swap audio back to the larger picture, press the Back button (Siri Remote 2nd generation or later) or button (Siri Remote 1st generation).
Move the viewer to any corner of the screen: Press the TV button on the Siri Remote, then select the onscreen move button to relocate the viewer to a new corner. Select again to move it to the next corner, and so on.
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In answering this simple question the result was me reviewing my notes like Charlie Day in the infamous Pepe Silvia skit. I realised to properly answer that question I would need to make the value of these AI projects and research papers a little more tangible, and the benefits more measurable and this would require a different format to my recent posts online
Although I try to share one or two generative AI-related projects per week (particularly those that lend themselves to the design studio), I appreciate how overwhelming it can be to monitor and review every machine learning development with the time and attention they deserve given the volume of information published on a weekly basis.
Within my creative circles, most of the interest has been understandably focused on image-generation tools. While text-to-image (T2I) platforms have indeed opened up new ways to explore design, my concern is that most within my peer group are concentrating on one area at the expense of the wider benefits AI can offer. To understand why this space is attracting investment, it's important to appreciate the real value of these paradigm-shifting platforms lies in their underlying technology. Recent advances in neural networks (NNs), large language models (LLMs), natural language processing (NLP), diffusion models, generative adversarial networks (GAN), transformers etc are the driving force behind this T2I revolution, but these technologies are far more sophisticated than image creation alone. This appreciation of the wider ecosystem should help justify the level of enterprise investment, but that extra knowledge will also make it easier for creatives to decide which AI tools/models to include in their own pipeline to primarily enhance the creative output they enjoy, but also automate, simplify and potentially replace the more mundane tasks. Members of my own team have already optimised how they generate pitch decks, tax reports, training syllabi, fielding support, technical writing, blogs, software plugins and even patent templates with AI-powered services, all of which result in more time for creativity.
Although every tech revolution has casualties, in my opinion, these technologies will replace tasks, not people. If you're a novice in a given field (not just design) AI can accelerate you to the point of productivity. If you've already done your '10,000 hours' and possess significant domain expertise and experience in a given field, these tools can make you an order of magnitude more efficient. In my opinion, this is more of a 'rising tides raise all boats' event and less of a job tsunami, and I believe that 'rising tide' will impact the shoreline of every sector that values efficiency.
With two of the biggest players Stability AI & Midjourney dominating the headlines with the release StableDiffusion 2.1 and V4 respectively, all things connected to the generative AI space are showing no signs of slowing. Although I'm a user of both, ignore OpenAI at your peril. With a portfolio of projects including #Dalle2, #GPT3, #WebGPT, #Whisper, the Playground and #GPT4 seemingly just around the corner, despite the competition, OpenAI still currently presents the most compelling, enterprise focussed offering.
Don't take my word for it, Replit & Jasper.AI built directly on top of GPT-3 already boast valuations of around $1B. Although not universally loved GitHub Copilot has fundamentally disrupted the way programmers write code, and Microsoft has already integrated functionality from OpenAI into other solutions under their umbrella such as Bing, Designer and Excel but the Azure OpenAI service introduced last year provides the clearest signal of long-term intent from Microsoft.
I also have to caveat the optimism of this article (and some of my recent posts) by also firmly stating that I don't believe all generative AI applications are created equally. With a rising number of solutions providing tangible value to their users, the advances in AI, particularly NLP, diffusion and LLMs are very real. With that said, I expect the vast majority of projects that emerge in the coming months won't have much impact at all. For every Jasper, Adept or Copilot offering genuine utility, there will be another 20 (some good, some bad, some scams) destined for short-term hype and eventual failure. That's just the nature of any perceived gold rush, when society seeks a quick buck (be that .com, crypto, metaverse or tulips) vaporware will inevitably follow. So I encourage us all to develop some critical thinking toward the space and identify the 'picks and shovels' platforms that can provide you and your organisation demonstrable utility. I also completely understand the deep routed public concerns and scepticism surrounding many of the generative AI platforms that have dominated the conversation. In addition to the genuine ethical debates that require continued discussion, many of us of a certain vintage still suffer from the PTSD inflicted by our first introduction to an 'AI assistant'..... Clippy.
Although many headlines might have you believe otherwise, the emergence of accessible AI models is neither messianic or the herald of disaster, the polarisation we are witnessing is a social phenomenon that occurs during every major technological shift which impacts all of us. Things are never as black and white as they are presented with the truth and clearest minds typically residing somewhere in the grey (or the blue below).
The remainder of this article aims to bring together a collection of seemingly disparate AI projects into a cohesive strategy for a company, and demonstrate the tangible value these tools offer. It would be easy to pick any company and replace a few tasks, but to see the far-reaching impact of generative AI the company selected should be able to feasibly implement the suggested solutions. Therefore the chosen company should possess the appropriate culture, data, distribution model and appetite to adopt this technology into their pipeline. The selected company must also be well-known enough for readers (of all technical levels) to understand how AI can enhance their business and/or staff in their roles. That way we can more accurately examine the impact of generative ai tools, while hopefully making the complexities of Ai more digestible when discussed in the context of a company (or specific job role). My aim in this article is to make it easier for anyone new to the space to see tangible use cases and hopefully demystify some of the jargon.
In July, Netflix named Microsoft as the 'exclusive technology and sales partner' to help power their first ad-supported tier. While my interest back then was little more than a passing one, a lot can happen in a few months and today that partnership looks a lot more interesting. I appreciate the announcement from Netflix refers to their sales partnership, but let's imagine this partnership extends beyond that to include OpenAI (and the wider Microsoft ecosystem). Now when reviewing all the players involved, it feels like a perfect relationship greater than the sum of its parts. One that could see Netflix leverage their platform, IP and an established culture of using big data, with #Microsoft's perfectly positioned technology partnership with #OpenAI (and NVIDIA but more on that later). In this thought experiment, let's examine how the products and research developed by Open AI could be deployed by Netflix to improve customer experience and business efficiency.
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