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Karlyn Hemmerling
When you launch Netflix on XB1, it shows your most recently watched show on the top left-hand side of the screen. Clicking on this tab will resume the most recent episode you watched, but as far as I can tell there is absolutely NO WAY to get back to the screen where you can choose a different episode to watch.
While hammering buttons at one point, I hit B and it did take me to that screen, but that only happened once. Every time I hit B during an episode now, it just takes me back to the launch screen with the most recently watched episode in the top left again.
The only way I've found to consistently pick a different episode to watch is to scroll through my list of saved shows and click on the show from there. That's a royal pain in the ass when you have as many shows saved on your list as me.
It's almost a non-issue considering shows look better on my 360 and PS4 than they do on the XB1 on Netflix. The XB1 over darkens the picture for some odd reason. But occassionally I can't be arsed to switch consoles after I've been playing a game on the XB1 and want to watch an episode of The 4400 or something...
I think to change episode, you have to actually find the show either through the search function, or via one of the other tabs. From my experience this is the only way, and you cannot change episode if you resume from the "Recently Watched" section. I had the same problem whereby it skipped an episode of Sons of Anarchy, and then wouldn't let me choose another unless I found SoA via search. Hopefully that makes sense.
I personally put the shows that I am currently watching, at the top of my list on the computer, which makes them appear at the top of the list on the Xbox One as well. You can then simply click on the show at the top of the list on the Xbox One, and select the episode that you want to watch.
You can switch episodes if you find it in the "my shows" tab that has all your saved shows/movies on it, but since that tab is extremely disorganized (why doesn't it sort them by date added to the list or alphabetically or something??) it's still a pain. Still it's better than having to type it into the 'search' function.
Still can't believe they didn't just mirror the various other Netflix apps and had to recreate the wheel, thereby screwing it up. I dunno if they'll fix it asap though. I mean it's already been out for 3 months lol.
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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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