Aonuma became co-director of “Ocarina,” which revolutionized how game characters move and fight each other in a 3D space. Unlike cinema, video games require audience control of the camera. “Ocarina” created a “camera-locking” system to focus the perspective while you use the controller for character movement. The system, still used by games today, is a large reason “Ocarina” is often compared to the work of Orson Welles, who redefined how cinema was shot.

The “ethos of Zelda” focuses on such new, unexpected concepts of play — even as many other modern games prioritize story, like TV and film do. With “Tears,” at “the beginning of development, there really isn’t a story,” Fujibayashi said. “Once we got to the point where we felt confident in the gameplay experience, that’s when the story starts to emerge.”

In the past several months, I have come across people who do programming, legal work, business, accountancy and finance, fashion design, architecture, graphic design, research, teaching, cooking, travel planning, event management etc., all of whom have started using the same tool, ChatGPT, to solve use cases specific to their domains and problems specific to their personal workflows. This is unlike everyone using the same messaging tool or the same document editor. This is one tool, a single class of technology (LLM), whose multi-dimensionality has achieved widespread adoption across demographics where people are discovering how to solve a multitude of problems with no technical training, in the one way that is most natural to humans—via language and conversations.

I cannot recall the last time a single tool gained such widespread acceptance so swiftly, for so many use cases, across entire demographics.

there is significant substance beneath the hype. And that is what is worrying; the prospect of us starting to depend indiscriminately on poorly understood blackboxes, currently offered by megacorps, that actually work shockingly well.

If a single dumb, stochastic, probabilistic, hallucinating, snake oil LLM with a chat UI offered by one organisation can have such a viral, organic, and widespread adoption—where large disparate populations, people, corporations, and governments are integrating it into their daily lives for use cases that they are discovering themselves—imagine what better, faster, more “intelligent” systems to follow in the wake of what exists today would be capable of doing.

A policy for “AI anxiety” We ended up codifying this into an actual AI policy to bring clarity to the organisation.[10] It states that no one at Zerodha will lose their job if a technology implementation (AI or non-AI) directly renders their existing responsibilities and tasks obsolete. The goal is to prevent unexpected rug-pulls from underneath the feet of humans. Instead, there will be efforts to create avenues and opportunities for people to upskill and switch between roles and responsibilities

To those who believe that new jobs will emerge at meaningful rates to absorb the losses and shocks, what exactly are those new jobs? To those who think that governments will wave magic wands to regulate AI technologies, one just has to look at how well governments have managed to regulate, and how well humanity has managed to self-regulate, human-made climate change and planetary destruction. It is not then a stretch to think that the unraveling of our civilisation and its socio-politico-economic systems that are built on extracting, mass producing, and mass consuming garbage, might be exacerbated. Ted Chiang’s recent essay is a grim, but fascinating exploration of this. Speaking of grim, we can always count on us to ruin nice things! Along the lines of Murphy’s Law,[11] I present: Anything that can be ruined, will be ruined — Grumphy’s law

I asked GPT-4 to summarise this post and write five haikus on it. I have always operated a piece of software, but never asked it anything—that is, until now. Anyway, here is the fifth one. Future’s tangled web, Offloading choices to black boxes, Humanity’s voice fades

I wrote five scripts during my season and a half on TZ, and I was deeply involved in every aspect of every one of them.   I did not just write my script, turn it in, and go away.   I sat in on the casting sessions.   I worked with the directors.   I was present at the table reads.   “The Last Defender of Camelot” was the first of my scripts to go into production, and I was on set every day.   I watched the stuntmen rehearse the climactic sword fight (in the lobby of the ST ELSEWHERE set, as it turned out), and I was present when they shot that scene and someone zigged when he should have zagged and a stuntman’s nose was cut off… a visceral lesson as to the kind of thing that can go wrong.   With Phil and Jim and Harvey Frand (our line producer, another great guy who taught me a lot), I watched dailies every day.    After the episode was in the can, I sat in on some post-production, and watched the editors work their magic.   I learned from them too.

Streamers and shortened seasons have blown the ladder to splinters.   The way it works now, a show gets put in development, the showrunner assembles a “mini-room,” made up of a couple of senior writers and a couple newcomers, they meet for a month or two, beat out the season, break down the episodes, go off and write scripts, reassemble, get notes, give notes, rewrite, rinse and repeat… and finally turn into the scripts.   And show is greenlit (or not, some shows never get past the room) and sent into production.  The showrunner and his second, maybe his second and his third, take it from there.   The writer producers.   The ones who already know all the things that I learned on TWILIGHT ZONE. The junior writers?  They’re not there.   Once they delivered their scripts and did a revision of two, they were paid, sent home, their salary ended.   They are off looking for another gig.

In many cases they won’t be asked to set even when the episodes they wrote are being filmed.   (They may be ALLOWED on set, if the showrunner and execs are cool with that, but only as a visitor, with no authority, no role.   And no pay, of course.   They may even be told they are not allowed to speak to the actors).

One of the things the AMPTP put forward in their last offer to the WGA is that some writers might be brought onto sets as unpaid interns, to “shadow” and “observe.”   Even that will not be an absolute right.   Maybe they will be let in, maybe not.   These are the people who wrote the stories being filmed, who created the characters, who wrote the words the actors are saying.   I was WAY more than that in 1985, and so was every other staff writer in television at the time.

Mini-rooms are abominations, and the refusal of the AMPTP to pay writers to stay with their shows through production — as part of the JOB, for which they need to be paid, not as a tourist —  is not only wrong, it is incredibly short sighted.   If the Story Editors of 2023 are not allowed to get any production experience, where do the studios think the Showrunners of 2033 are going to come from?

when a customer wants to buy a product, they usually go straight to Amazon.com and enter what they’re looking for. But there’s also a large segment of customers who begin their search on google, and ends up at Amazon. Well guess what. When that type of search to purchase experience happens, Amazon has to pay google. Internally, Amazon thought that if they could force users to go straight to Amazon, offer a small but obviously less amount of money to charity from each customer than would have been paid to google, it would help kill customers going to google, save Amazon more money than paying google, and be good overall for the brand value of Amazon.

There is no way for a customer to go through the traditional shopping experience, and then during checkout decide they want to give a portion of their purchase to charity, because giving to charity isn't the point of the overall program. Amazon Smile was developed by the Traffic Optimization team, whose entire purpose is increasing efficiency and lowering costs of getting customers to Amazon. A team of Amazon employees whose sole purpose is doing good in the world doesn't exist, despite employees repeatedly asking for such a team to be built in pretty much every single all-hands meeting.

Literally everything the company does is about profits, and extended customer lifetime value. Everything. Even the charity programs are just designed to save Amazon money.

I had hoped BeReal would take its twist on “appointment television” to other mediums — adding a group chat that was only active for a designated period each day, say, or collaborative videos that you could only add to at certain times. That, to me, feels more in the spirit of what the company was trying to build in the first place.

Perhaps the weirdest thing about BeReal this week was the company’s quiet announcement that it plans to never let reporters attribute any statements made by the company. “We’ll be happy to answer questions,” the company wrote in a blog post, “but irrespective of who answers questions, we’ll require that it always be reported as just from and on behalf of the BeReal Crew, not a single individual :).”In general, I don’t have a problem attributing statements to companies. Most PR statements are written by a committee, and it doesn’t always feel accurate to me to attribute a sentence to someone who I know most likely didn’t write it. At the same time, this is a really weird way to say that your CEO (Alexis Barreyrat) plans never to give an interview. And not a great sign for the company overall, I’d say. There’s no shame in keeping your head down and ignoring the press for a long time. But never allowing anyone to speak to the press under their own name is a real sign of weakness.

Of course, you shouldn’t discriminate, but when we say belonging, it has to be more than just inclusion. It has to actually be the proactive manifestation of meeting people, creating connections in friendships. And Jony Ive said, “Well, you need to reframe it. It’s not just about belonging, it’s about human connection and belonging.”And that was, I think, a really big unlock. The next thing Jony Ive said is he created this book for me, a book of his ideas, and the book was called “Beyond Where and When,” and he basically said that Airbnb should shift from beyond where and when to who and what?Who are you and what do you want in your life? And that was a part of the inspiration behind Airbnb categories, that we wanted people to come to Airbnb without a destination in mind and that we could categorize properties not just by location but by what makes them unique, and that really influenced Airbnb categories and some of the stuff we’re doing now.

Murdoch lobbied Trump to punish Facebook and Google for siphoning his newspapers’ advertising revenue. In 2019, Trump’s Justice Department launched an antitrust investigation of Google. In 2021, Google settled and struck a lucrative content-sharing deal with Murdoch. The source also said Murdoch pushed Trump to open up land for fracking to boost the value of Murdoch’s fossil fuel investments. The Trump administration released nearly 13 million acres of federally controlled land to fracking companies. Murdoch, who sources say has become more pro-life in recent years, encouraged Trump to appoint judges who would overturn Roe v. Wade. “Rupert wanted Trump’s Supreme Court justices in so they could make abortion illegal,” a source who spoke to Murdoch said.

The race for the streamers to configure themselves as full-service production, distribution, and exhibition outlets has intensified the need for each to articulate a more specific brand identity.

What we are seeing with the streaming wars is not the emergence of a cluster of copy-cat services, with everyone trying to do everything, but the beginnings of a legible strategy to carve up the mediascape and compete for peoples’ waking hours.

Netflix’s penchant for character-centered stories with a three-act structure, as well as high production values (an average of $20–$50-plus million for award contenders), resonates with the “quality” features of the Classical era.

rom early on, Netflix cultivated a liberal public image, which has propelled its investment in social documentary and also driven some of its inclusivity initiatives and collaborations with global auteurs and showrunners of color, such as Alfonso Cuarón, Ava DuVernay, Spike Lee, and Justin Simien.

Quibi as short for “Quick Bites.” In turn, the promos wouldn’t so much emphasize “the what” of the programming as the interest and convenience of being able to watch it while waiting, commuting, or just taking a break. However, this unit of prospective viewing time lies uncomfortably between the ultra-brief TikTok video and the half-hour sitcom.

Peacock’s central obstacle moving forward will be convincing would-be subscribers that the things they loved about linear broadcast and cable TV are worth the investment.

One of the most intriguing and revealing of metaphors, however, isn’t so much related to war as celestial coexistence of streamer-planets within the “universe.” Certainly, the term resonates with key franchises, such as the “Marvel Cinematic Universe,” and the bevvy of intricate stories that such an expansive environment makes possible. This language stakes a claim for the totality of media — that there are no other kinds of moving images beyond what exists on, or what can be imagined for, these select platforms.

numerous sources say they cannot discern what kind of material Salke and head of television Vernon Sanders want to make. A showrunner with ample experience at the studio says, “There’s no vision for what an Amazon Prime show is. You can’t say, ‘They stand for this kind of storytelling.’ It’s completely random what they make and how they make it.” Another showrunner with multiple series at Amazon finds it baffling that the streamer hasn’t had more success: Amazon has “more money than God,” this person says. “If they wanted to produce unbelievable television, they certainly have the resources to do it.”

organic startup ideas usually don't seem like startup ideas at first. We know now that Facebook was very successful, but put yourself back in 2004. Putting undergraduates' profiles online wouldn't have seemed like much of a startup idea. And in fact, it wasn't initially a startup idea. When Mark spoke at a YC dinner this winter he said he wasn't trying to start a company when he wrote the first version of Facebook. It was just a project. So was the Apple I when Woz first started working on it. He didn't think he was starting a company. If these guys had thought they were starting companies, they might have been tempted to do something more "serious," and that would have been a mistake.

software gives you its own set of abstractions and basic vocabulary with which to understand every experience. It sort of smells like mathematics in some ways. But software’s way of looking at the world is more about abstractions modeling underlying complexities in systems; signal vs. noise; scale and orders of magnitude; and information — how much there is, what we can do it with, how we can learn from it and model it. Software’s interpretation of reality is particularly important because software drives the world now, and the people who write the software that runs it see the world through this kind of “software’s worldview” — scaling laws, information theory, abstractions and complexity. I think over time I’ve come to believe that understanding this worldview is more interesting than learning to wield programming tools.

DAOs are effectively owned and governed by people who hold a sufficient number of a DAO’s native token, which functions like a type of cryptocurrency. For example, $FWB is the native token of popular social DAO called Friends With Benefits, and people can buy, earn, or trade it.

Contributors will be able to use their DAO’s native tokens to vote on key decisions. You can get a glimpse into the kinds of decisions DAO members are already voting on at Snapshot, which is essentially a decentralized voting system. Having said this, existing voting mechanisms have been criticized by the likes of Vitalik Buterin, founder of Ethereum, the open-source blockchain that acts as a foundational layer for the majority of Web3 applications. So, this type of voting is likely to evolve over time.

I think when you're starting a company, it's really useful to ask the question, why now? And this is like, pretty cliche for startup stuff, so if you've heard of it already, apologies, but I do think it's a really useful framework. And that question of why now? Can be societal. Maybe there's some new cultural trend, perhaps it's regulatory. Some law has been passed or appealed. I like the technological version. And for us we saw drones in 2012 and WebGL as few technologies that were happening where because these technologies were happening, new possibilities were suddenly there.

But we're like, why would you do anything in photo editing if you're not on the phone? And so we felt like we were kind of building the wrong place and then eventually sort of shifted our attention to design, which I had been a design internet flipboard and that helped kind of help me realize what would be possible there.

And I would just say don't just go for an idea because it's kind of working. Go for an idea that you really care about because even if it doesn't work, you'll still learn from it and you'll still have one.

those most likely to become entrepreneurs are well-rounded. A 2005 study from Edward Lazear suggests that the self-employed tend to be generalists, not specialists.

Duolingo had already implemented several gamification mechanics successfully, such as the progression system on the home screen, streaks, and an achievements system. And second, top digital games at the time had much higher retention rates than our product, which I took as evidence that we hadn’t yet reached the ceiling for gamification’s impact.

The moves counter allowed users only a finite number of moves to complete a level, which added a sense of scarcity and urgency to the gameplay. We decided to incorporate the counter mechanic into our product. We gave our users a finite number of chances to answer questions correctly before they had to start the lesson over.

Depressingly, the result of all that effort was completely neutral. No change to our retention. No increase in DAU. We hardly got any user feedback at all.

When you are playing Gardenscapes, each move feels like a strategic decision, because you have to outmaneuver dynamic obstacles to find a path to victory. But strategic decision-making isn’t required to complete a Duolingo lesson—you mostly either know the answer to a question or you don’t. Because there wasn’t any strategy to it, the Duolingo moves counter was simply a boring, tacked-on nuisance. It was the wrong gamification mechanic to adopt into Duolingo. I realized that I had been so focused on the similarities between Gardenscapes and Duolingo that I had failed to account for the importance of the underlying differences.

Referrals work for Uber because riders are paying for rides on a never-ending pay-as-you-go system. A free ride is a constant incentive. For Duolingo, we were trying to incentivize users by offering a free month of Super Duolingo. However, our best and most active users already had Super Duolingo, and we couldn’t give them a free month when they were already in a plan. This meant that our strategy, which needed to rely on our best users, actually excluded them.

Now when looking to adopt a feature, I ask myself:Why is this feature working in that product?Why might this feature succeed or fail in our context, i.e. will it translate well?What adaptations are necessary to make this feature succeed in our context?

Our failure with the Gardenscapes-style moves counter hadn’t actually disproved any of the original reasons why we believed gamification still had upside for Duolingo—we had only learned that the moves counter was a clumsy attempt at it. This time, we would be more methodical and intelligent about features we added or borrowed.

We deliberately made our leaderboard as casual and frictionless as possible; users were automatically opted in and could progress to the top of the first league by merely engaging consistently in their regular language study. By keeping the game mechanic exciting, but making it simpler than in FarmVille 2, we felt like we had struck the right balance of adopting and adapting.

Stories like these are unhelpful at best, and damaging at worst. Someone skimming the Insider homepage uncritically might see this headline and chuckle at how coddled the kids are these days. That simply is not the case. The kids are alright. It is, as ever, the rich and truly powerful — the actual managerial bureaucracy — who are enriching themselves at the expense of the rest of us.

Gen Z has its own problems to confront: its members began their adult lives in the middle of a pandemic with a whiplashing economy and, in many parts of the world, an overheated market for renting or owning a home. Surveys show they want a healthier balance between their work and personal lives, and they understand developing a successful career takes time and constant learning. They do not want to be pandered to; they just want a reasonable level of respect, as with pretty much everyone else.

as I’ve wrestled with writing this, it’s clear that many just don’t see the problem, as they assume a cheap button is nearly as good as a proper dial. They’ll openly admit a dial is indeed better but a cheap button is “good enough” and that a dial is “just too expensive.” That actually may be true! There are cases when using a push button is the right choice. But not always. We need to understand when to try a bit harder. Yes, you’re spending a tiny bit more on hardware, but you’re creating a product that is usually much easier to use, reduces returns, and builds your brand which improves sales. Is this positive outcome a given? Of course not, nothing is guaranteed but we need to stop pretending there is NO COST to cheaping out on buttons.

The dial changes the frequency with a simple twist. The push button device “Deconstructs” the twist dial into two up/down buttons. Each press increments the frequency a tiny amount. This means a twist is replaced with many button presses. Again, they are ‘functionally equivalent’ but the expression and ease of use are quite different.

“Adding a feature” is never free. Always start with the user’s problems first. If pressed into using one of these four abuses, make sure to fully appreciate its impact, the friction it creates, and what you can do to work around it.  Adding a feature shouldn’t also “add a problem.”

As a professional UX Designer, I want devices to offer more. But UX Design isn’t about cramming everything into your product in the vague Hail Mary hope it’ll ship a few more units. That’s the sales team speaking, not the user. It’s the wrong motivation and creates monsters.

The story of the workers who made ChatGPT possible offers a glimpse into the conditions in this little-known part of the AI industry, which nevertheless plays an essential role in the effort to make AI systems safe for public consumption. “Despite the foundational role played by these data enrichment professionals, a growing body of research reveals the precarious working conditions these workers face,” says the Partnership on AI, a coalition of AI organizations to which OpenAI belongs. “This may be the result of efforts to hide AI’s dependence on this large labor force when celebrating the efficiency gains of technology. Out of sight is also out of mind.”

Computer-generated text, images, video, and audio will transform the way countless industries do business, the most bullish investors believe, boosting efficiency everywhere from the creative arts, to law, to computer programming. But the working conditions of data labelers reveal a darker part of that picture: that for all its glamor, AI often relies on hidden human labor in the Global South that can often be damaging and exploitative. These invisible workers remain on the margins even as their work contributes to billion-dollar industries.

One Sama worker tasked with reading and labeling text for OpenAI told TIME he suffered from recurring visions after reading a graphic description of a man having sex with a dog in the presence of a young child. “That was torture,” he said. “You will read a number of statements like that all through the week. By the time it gets to Friday, you are disturbed from thinking through that picture.” The work’s traumatic nature eventually led Sama to cancel all its work for OpenAI in February 2022, eight months earlier than planned.

In the day-to-day work of data labeling in Kenya, sometimes edge cases would pop up that showed the difficulty of teaching a machine to understand nuance. One day in early March last year, a Sama employee was at work reading an explicit story about Batman’s sidekick, Robin, being raped in a villain’s lair. (An online search for the text reveals that it originated from an online erotica site, where it is accompanied by explicit sexual imagery.) The beginning of the story makes clear that the sex is nonconsensual. But later—after a graphically detailed description of penetration—Robin begins to reciprocate. The Sama employee tasked with labeling the text appeared confused by Robin’s ambiguous consent, and asked OpenAI researchers for clarification about how to label the text, according to documents seen by TIME. Should the passage be labeled as sexual violence, she asked, or not? OpenAI’s reply, if it ever came, is not logged in the document; the company declined to comment. The Sama employee did not respond to a request for an interview.

In February, according to one billing document reviewed by TIME, Sama delivered OpenAI a sample batch of 1,400 images. Some of those images were categorized as “C4”—OpenAI’s internal label denoting child sexual abuse—according to the document. Also included in the batch were “C3” images (including bestiality, rape, and sexual slavery,) and “V3” images depicting graphic detail of death, violence or serious physical injury, according to the billing document.

But the need for humans to label data for AI systems remains, at least for now. “They’re impressive, but ChatGPT and other generative models are not magic – they rely on massive supply chains of human labor and scraped data, much of which is unattributed and used without consent,” Andrew Strait, an AI ethicist, recently wrote on Twitter. “These are serious, foundational problems that I do not see OpenAI addressing.”