Podcast appearances and mentions of charlie steiner

Tim Cates gets you ready before the Dodgers face the Phillies in Game 1 of the NLDS. Dave Roberts talks about the roster moves. Will Smith gives an update on his hand. Charlie Steiner and Rick Monday preview the series. DV chats with Mookie Betts.

Tim Cates walks you up to first pitch between the Dodgers and Dbacks. Dave Roberts talks about activating Roki Sasaki and sending Kirby Yates to the IL. Charlie Steiner and Rick Monday talk about the bullpen's struggles. DV chats with Justin Wrobleski. 

Tim Cates walks you up to first pitch between the Dodgers and Dbacks. Dave Roberts talks about activating Roki Sasaki and sending Kirby Yates to the IL. Charlie Steiner and Rick Monday talk about the bullpen's struggles. DV chats with Justin Wrobleski. 

Tim Cates gets you ready before the Dodgers start a 4-game series against the Giants. Clayton Kershaw announces his retirement after 18 seasons. Freddie Freeman and Max Muncy talk about Clayton's Hall of Fame career. Charlie Steiner and Rick Monday share their memories of Kershaw. Chase Utley talks about being teammates with Clayton. 

Tim Cates gets you ready before the Dodgers start a 4-game series against the Giants. Clayton Kershaw announces his retirement after 18 seasons. Freddie Freeman and Max Muncy talk about Clayton's Hall of Fame career. Charlie Steiner and Rick Monday share their memories of Kershaw. Chase Utley talks about being teammates with Clayton. 

Tim Cates gets you ready for the 3-game series between the Dodgers and Phillies. Charlie Steiner and Rick Monday preview the series. DV chats with Dodgers hitting coach, Aaron Bates. 

Tim Cates gets you ready for the 3-game series between the Dodgers and Phillies. Charlie Steiner and Rick Monday preview the series. DV chats with Dodgers hitting coach, Aaron Bates. 

Tim Cates gets you ready before the Dodgers start a 3-game series in San Francisco. Dave Roberts gives an update on Will Smith's bone bruise. Charlie Steiner and Rick Monday talk about the rivalry against the Giants. DV chats with Freddie Freeman on Freddie's birthday. 

Tim Cates gets you ready before the Dodgers start a 3-game series in San Francisco. Dave Roberts gives an update on Will Smith's bone bruise. Charlie Steiner and Rick Monday talk about the rivalry against the Giants. DV chats with Freddie Freeman on Freddie's birthday. 

Tim Cates gets you ready before the Dodgers start a 3-game series against the Rockies. Max Muncy returns to the lineup. Charlie Steiner and Rick Monday talk about the 1-5 road trip. DV chats with Ben Rortvedt.

Tim Cates gets you ready before the Dodgers start a 3-game series against the Rockies. Max Muncy returns to the lineup. Charlie Steiner and Rick Monday talk about the 1-5 road trip. DV chats with Ben Rortvedt.

Tim Cates gets you ready before the Dodgers start a 3-game series against the Orioles. Dave Roberts talks about Tyler Glasnow's back. Charlie Steiner and Rick Monday preview the series in Baltimore. DV chats with baseball insider, Buster Olney. 

Tim Cates gets you ready before the Dodgers start a 3-game series against the Orioles. Dave Roberts talks about Tyler Glasnow's back. Charlie Steiner and Rick Monday preview the series in Baltimore. DV chats with baseball insider, Buster Olney. 

Tim Cates gets you ready before the Dodgers start a 3-game series against the Pirates. Kirsten's Corner. A Matt Kemp Hoffy Magical Moment. Charlie Steiner and Rick Mondy preview the series.

Tim Cates gets you ready before the Dodgers start a 3-game series against the Pirates. Kirsten's Corner. A Matt Kemp Hoffy Magical Moment. Charlie Steiner and Rick Mondy preview the series.

Tim Cates gets you ready before the Dodgers start a 3-game series against the Reds. Kirsten's Corner. Charlie Steiner and Rick Monday preview the series. DV catches up with Kirby Yates. 

Tim Cates gets you ready before the Dodgers start a 3-game series against the Reds. Kirsten's Corner. Charlie Steiner and Rick Monday preview the series. DV catches up with Kirby Yates. 

Tim Cates gets you ready for the series finale between the Dodgers and Padres. A Hoffy Magical Moment from 1992.  Charlie Steiner catches up with Rick Monday. DV chats with newest Dodger, Buddy Kennedy. 

Tim Cates gets you ready for the series finale between the Dodgers and Padres. A Hoffy Magical Moment from 1992.  Charlie Steiner catches up with Rick Monday. DV chats with newest Dodger, Buddy Kennedy. 

Tim Cates gets you ready before the Dodgers start a massive 3-game series against the Padres. Dave Roberts talks about putting Max Muncy on the IL. Rick Monday and Charlie Steiner preview the huge series. DV catches up with Freddie Freeman. 

Tim Cates gets you ready before the Dodgers start a massive 3-game series against the Padres. Dave Roberts talks about putting Max Muncy on the IL. Rick Monday and Charlie Steiner preview the huge series. DV catches up with Freddie Freeman. 

Sal and BT dove into the world of iconic home run calls, prompted by a discussion of Gary Cohen's "on his own private iceberg" line for Pete Alonso's record-breaking home run. The conversation took a fiery turn when they brought in the legendary John Sterling, who revealed the shocking backstory behind the famous Aaron Boone walk-off home run call. Sterling recounted his frustration when his then-partner Charlie Steiner called the home run and then "jumped in" on his signature "Yankees win!" call, a move that Sterling claims Steiner admitted he "always wanted to do." The exchange shed light on the often-fierce, competitive world of sports broadcasting and the deep-seated rivalries that can exist behind the mic.

BT and Sal ripped into the broadcast calls for Pete Alonso's record-breaking home run, focusing on what they felt was a pre-meditated, scripted call from SNY's Gary Cohen. BT argued that the "on his own private iceberg" line was "corny," a sentiment that Sal, despite his affection for Cohen, seemed to agree with. The duo contrasted the TV call with the radio broadcast, praising Keith Hernandez's more organic and fiery reaction. They also dove into a historic Yankees call by John Sterling, and the awkward moment when his partner Charlie Steiner interjected, highlighting the difference between a great, unscripted call and one that feels manufactured.

Tim Cates gets you ready before the Dodgers start a 3-game series against the Blue Jays. A historic matchup between two members of the 3,000 K club Clayton Kershaw and Max Scherzer. Charlie Steiner and Rick Monday talk about the matchup between two future Hall of Famers. DV catches up with Blake Treinen who was teammates with both pitchers. 

Tim Cates gets you ready before the Dodgers start a 3-game series against the Blue Jays. A historic matchup between two members of the 3,000 K club Clayton Kershaw and Max Scherzer. Charlie Steiner and Rick Monday talk about the matchup between two future Hall of Famers. DV catches up with Blake Treinen who was teammates with both pitchers. 

TIm Cates gets you ready before the Dodgers start a 3-game series against the Cardinals. Kirsten's Corner. Charlie Steiner catches up with Rick Monday. DV chats with Blake Snell. 

TIm Cates gets you ready before the Dodgers start a 3-game series against the Cardinals. Kirsten's Corner. Charlie Steiner catches up with Rick Monday. DV chats with Blake Snell. 

Tim Cates gets you ready for the final game of the Dodgers-Red Sox series in Boston. Rick has a pregame preview with Charlie Steiner. DV catches up with Will Smith. 

Tim Cates gets you ready for the final game of the Dodgers-Red Sox series in Boston. Rick has a pregame preview with Charlie Steiner. DV catches up with Will Smith. 

Tim Cates gets you ready for the rubber game between the Dodgers and Giants. Charlie Steiner and Rick Monday talk about Shohei Ohtani, DV catches up with Dino Ebel. 

Tim Cates gets you ready for the rubber game between the Dodgers and Giants. Charlie Steiner and Rick Monday talk about Shohei Ohtani, DV catches up with Dino Ebel. 

Tim Cates gets you ready for the series finale between the Dodgers and Astros. A Hoffy Magical Moment from 1942. Charlie Steiner reunites with Rick Monday. DV catches up with Blake Treinen. 

Tim Cates gets you ready for the series finale between the Dodgers and Astros. A Hoffy Magical Moment from 1942. Charlie Steiner reunites with Rick Monday. DV catches up with Blake Treinen. 

This morning on The Greg & Dan Show, Dr. Paul Guilfor joined us in the studio to share some information about the upcoming Charlie Steiner Symposium for sports communication next week.See omnystudio.com/listener for privacy information.

Greg and Dan talk to Josh Dickhaus from Bradley University about the upcoming annual Charlie Steiner Symposium.See omnystudio.com/listener for privacy information.

Peter Grunawalt recounts his 39-day paddle to Hudson Bay alongside fellow Camp Voyageur alumni Elliot Keller, Charlie Steiner, and friend Matt Fossand. Setting off on June 15th, 2014, from the shores of Camp's bay, the team navigated rugged landscapes, wild rivers, and vast wilderness, arriving in Northeastern Canada on July 20th. Peter shares the challenges, triumphs, and life lessons gained from their extraordinary expedition.  Check out their route here and trip video here."Text us feedback."Co-hosts Alex Kvanli & John Burgman discuss all-things related to Camp Voyageur in Ely, Minnesota. They share trail stories, interview Voyageur alumni, & reflect on the lore of the Great Northwoods. They also trade Boundary Waters travel tips & advice. Whether you're a former camper, a current camper, or an adventure enthusiast looking to improve your Boundary Waters experience, there's something for everyone in each episode. Can't get enough? Read our blog Find us on Facebook, Instagram, or YouTube Enroll your son at Camp Voyageur Work at Camp Voyageur 11 Proven Ways Wilderness Adventure Camps Can Transform Your Kid's Life by Alex Kvanli

Tony opens the show by reading a few emails, and then he talks about his friend Charlie Steiner revealing he has been battling cancer, but that it is now in remission. Jason La Canfora calls in to talk about a blown call in the Thursday Night game and the trade market, James Carville and Jeff Ma call in to make their weekly football picks, and Tony closes out the show by opening up the Mailbag. Song : MidLyfe's Crisis “Living 2 Out Of 7” To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

In our conversation, Kenny opens up about the tightrope walk of fitting in while standing out in the sports broadcasting world. He brings to life his experiences with iconic colleagues like Bob Lee, Charlie Steiner, and Dan Patrick, shedding light on how trust and authenticity play crucial roles in building a successful media career. We also reflect on the groundbreaking contributions of colleagues like Stuart Scott, whose cultural perspective forever changed sports broadcasting. Through Kenny's anecdotes, we gain an understanding of the balance required to cover both lighthearted and serious stories with equal care. (00:04 - 00:55) Legendary Reunion With Kenny Mayne (07:32 - 08:34) Fast Track to TV Broadcasting Career (11:39 - 13:08) Sports Night's Early Influence at ESPN (16:43 - 18:23) Impactful Personalities in Broadcasting (20:58 - 21:58) Main Event (37:57 - 39:12) Life After ESPN (42:55 - 43:54) Players' Impact on Professional Sports (47:32 - 48:23) Challenges Facing Sports Beat Reporters For more, be sure to visit Yyzsportsmedia.com and follow @yyzsportsmedia

Tony opens the show by talking about watching the indoor track world championships in Glasgow, a trip to the Candy Kitchen, the Golf from the weekend and the passing of Chris Mortensen. Michael Wilbon calls in to talk some more about Mort, and also about Caitlin Clark setting the NCAA scoring record, Charlie Steiner calls in to talk about the excitement surrounding the Dodgers this season and getting to call those games, and Tony closes out the show by opening up the Mailbag. Songs : Year of the Buffalo “Ohio River” ; “Hands that Bleed” To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Humans aren't fleeb., published by Charlie Steiner on January 24, 2024 on LessWrong. In the oceans of the planet Water, a species of intelligent squid-like aliens - we'll just call them the People - debate about what it means to be fleeb. Fleeb is a property of great interest to the People, or at least they think so, but they also have a lot of trouble defining it. They're fleeb when they're awake, but less fleeb or maybe not fleeb at all when they're asleep. Some animals that act clever are probably somewhat fleeb, and other animals that are stupid and predictable probably aren't fleeb. But fleeb isn't just problem-solving ability, because philosophers of the People have written of hypothetical alien lifeforms that could be good at solving problems without intuitively being fleeb. Instead, the idea of "fleeb" is more related to how much a Person can see a reflection of their own thinking in the processes of the subject. A look-up table definitely isn't fleeb. But how much of the thinking of the People do you need to copy to be more fleeb than their pet cuttlefish-aliens? Do you need to store and recall memories? Do you need emotions? Do you need to make choices? Do you need to reflect on yourself? Do you need to be able to communicate, maybe not with words, but modeling other creatures around you as having models of the world and choosing actions to honestly inform them? Yes to all of these, say the People. These are important things to them about their thinking, and so important for being fleeb. In fact, the People go even farther. A simple abacus can store memories if "memories" just means any record of the past. But to be fleeb, you should store and recall memories more in the sense that People do it. Similar for having emotions, making choices, etc. So the People have some more intuitions about what makes a creature fleeb: You should store and recall visual/aural/olfactory/electrosensory memories in a way suitable for remembering them both from similar sensory information and abstract reasoning, and these memories should be bundled with metadata like time and emotional valence. Your tactile/kinesthetic memories should be opaque to abstract reasoning (perhaps distributed in your limbs, as in the People), but can be recalled-in-the-felt-way from similar sensory information. It's hard to tell if you have emotions unless you have ones recognizable and important to the People. For the lowest levels of fleeb, it's enough to have a general positive emotion (pleasure) and a general negative one (pain/hunger). But to be fleeb like the People are, you should also have emotions like curiosity, boredom, love, just-made-a-large-change-to-self-regulation-heuristics, anxiety, working-memory-is-full, and hope. You should make choices similar to how the People do. Primed by your emotional state, you should use fast heuristics to reconfigure your cognitive pathway so you call on the correct resources to make a good plan. Then you quickly generate some potential actions and refine them until taking the best one seems better than not acting. Etc. When the People learned about humans, it sparked a lively philosophical debate. Clearly humans are quite clever, and have some recognizable cognitive algorithms, in the same way an AI using two different semantic hashes is "remembering" in a more fleeb-ish way than an abacus is. But compare humans to a pet cuttlefish-alien - even though the pet cuttlefish-alien can't solve problems as well, it has emotions us humans don't have even a dim analogue of, and overall has a more similar cognitive architecture to the People. Some brash philosophers of the People made bold claims that humans were fleeb, and therefore deserved full rights immediately. But cooler heads prevailed; despite outputting clever text signals, humans were just too different...

The best of nearly 100 interviews in “Tell me a story I don't know” is really a personal choice. I've featured so many guests in best of 9 seasons but in this finale I thought it might be worthy to have you listen to some thought provoking, funny and poignant moments. And not the least of them came from two people who left us. Dave Wills, the ever popular voice of the Tampa Rays and a Chicago native died last March of a heart ailment. He was only 58.Alan Schwartz was 91 but full of vim and vigor. He was once president of the United States Tennis Association and builder of Mid Town tennis in 1970 and for nearly 50 years, the largest indoor facility in the U.S. Schwartz died in December of 2022, just three days after we had our semi annual lunch. I was crushed when I learned of both of their passings.The best of also includes an almost hard to believe story from Los Angeles Dodgers play by play voice Charlie Steiner how history repeated itself. Cheryl Ray Stout, long time reporter and trailblazer here in Chicago recounted how she broke the story of Michael Jordan leaving basketball for baseball and then, returning to the Bulls!Cubs radio voice Ron Coomer remembered as a child how he refused to trade baseball gloves with a future hall of famer and how could I not include Brent Musburger, my inspiration back when I was a 14 year old entertaining thoughts of getting into the business. After spending a half century plying my trade, I thanked him publicly. It was all worth it.“Tell me a story I don't know" is sponsored by Mr. Duct and “Tell me a story I don't know: conversations with Chicago sports legends” is now available on Amazon Books and at chicago area book stores.It's been a great run of "Tell me story I don't know" with a special two part podcast coming up! Make sure not to miss any of the content on the Last Word on Sports Media podcast feed on Apple, Spreaker, Spotify, Google, etc.!

The best of nearly 100 interviews in “Tell me a story I don't know” is really a personal choice. I've featured so many guests in best of 9 seasons but in this finale I thought it might be worthy to have you listen to some thought provoking, funny and poignant moments. And not the least of them came from two people who left us. Dave Wills, the ever popular voice of the Tampa Rays and a Chicago native died last March of a heart ailment. He was only 58.Alan Schwartz was 91 but full of vim and vigor. He was once president of the United States Tennis Association and builder of Mid Town tennis in 1970 and for nearly 50 years, the largest indoor facility in the U.S. Schwartz died in December of 2022, just three days after we had our semi annual lunch. I was crushed when I learned of both of their passings.The best of also includes an almost hard to believe story from Los Angeles Dodgers play by play voice Charlie Steiner how history repeated itself. Cheryl Ray Stout, long time reporter and trailblazer here in Chicago recounted how she broke the story of Michael Jordan leaving basketball for baseball and then, returning to the Bulls!Cubs radio voice Ron Coomer remembered as a child how he refused to trade baseball gloves with a future hall of famer and how could I not include Brent Musburger, my inspiration back when I was a 14 year old entertaining thoughts of getting into the business. After spending a half century plying my trade, I thanked him publicly. It was all worth it.“Tell me a story I don't know" is sponsored by Mr. Duct and “Tell me a story I don't know: conversations with Chicago sports legends” is now available on Amazon Books and at chicago area book stores.It's been a great run of "Tell me story I don't know" with a special two part podcast coming up! Make sure not to miss any of the content on the Last Word on Sports Media podcast feed on Apple, Spreaker, Spotify, Google, etc.!

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Neural uncertainty estimation for alignment, published by Charlie Steiner on December 5, 2023 on The AI Alignment Forum. Introduction Suppose you've built some AI model of human values. You input a situation, and it spits out a goodness rating. You might want to ask: "What are the error bars on this goodness rating?" In addition to it just being nice to know error bars, an uncertainty estimate can also be useful inside the AI: guiding active learning[1], correcting for the optimizer's curse[2], or doing out-of-distribution detection[3]. I recently got into the uncertainty estimation literature for neural networks (NNs) for a pet reason: I think it would be useful for alignment to quantify the domain of validity of an AI's latent features. If we point an AI at some concept in its world-model, optimizing for realizations of that concept can go wrong by pushing that concept outside its domain of validity. But just keep thoughts of alignment in your back pocket for now. This post is primarily a survey of the uncertainty estimation literature, interspersed with my own takes. The Bayesian neural network picture The Bayesian NN picture is the great granddaddy of basically every uncertainty estimation method for NNs, so it's appropriate to start here. The picture is simple. You start with a prior distribution over parameters. Your training data is evidence, and after training on it you get an updated distribution over parameters. Given an input, you calculate a distribution over outputs by propagating the input through the Bayesian neural network. This would all be very proper and irrelevant ("Sure, let me just update my 2trilliondimensional joint distribution over all the parameters of the model"), except for the fact that actually training NNs does kind of work this way. If you use a log likelihood loss and L2 regularization, the parameters that minimize loss will be at the peak of the distribution that a Bayesian NN would have, if your prior on the parameters was a Gaussian[4][5]. This is because of a bridge between the loss landscape and parameter uncertainty. Bayes's rule says P(parameters|dataset)=P(parameters)P(dataset|parameters)/P(dataset). Here P(parameters|dataset)is your posterior distribution you want to estimate, and P(parameters)P(dataset|parameters) is the exponential of the loss[6]. This lends itself to physics metaphors like "the distribution of parameters is a Boltzmann distribution sitting at the bottom of the loss basin." Empirically, calculating the uncertainty of a neural net by pretending it's adhering to the Bayesian NN picture works so well that one nice paper on ensemble methods[7] called it "ground truth." Of course to actually compute anything here you have to make approximations, and if you make the quick and dirty approximations (e.g. pretend you can find the shape of the loss basin from the Hessian) you get bad results[8], but people are doing clever things with Monte Carlo methods these days[9], and they find that better approximations to the Bayesian NN calculation get better results. But doing Monte Carlo traversal of the loss landscape is expensive. For a technique to apply at scale, it must impose only a small multiplier on cost to run the model, and if you want it to become ubiquitous the cost it imposes must be truly tiny. Ensembles A quite different approach to uncertainty is ensembles[10]. Just train a dozen-ish models, ask them for their recommendations, and estimate uncertainty from the spread. The dozen-times cost multiplier on everything is steep, but if you're querying the model a lot it's cheaper than Monte Carlo estimation of the loss landscape. Ensembling is theoretically straightforward. You don't need to pretend the model is trained to convergence, you don't need to train specifically for predictive loss, you don't even need...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why it's so hard to talk about Consciousness, published by Rafael Harth on July 2, 2023 on LessWrong. [Thanks to Charlie Steiner, Richard Kennaway, and Said Achmiz for helpful discussion.] [Epistemic status: my best guess after having read a lot about the topic, including all LW posts and comment sections with the consciousness tag] There's a common pattern in online debates about consciousness. It looks something like this: One person will try to communicate a belief or idea to someone else, but they cannot get through no matter how hard they try. Here's a made-up example: "It's obvious that consciousness exists." Yes, it sure looks like the brain is doing a lot of non-parallel processing that involves several spatially distributed brain areas at once, so "I'm not just talking about the computational process. I mean qualia obviously exists." Define qualia. "You can't define qualia; it's a primitive. But you know what I mean." I don't. How could I if you can't define it? "I mean that there clearly is some non-material experience stuff!" Non-material, as in defying the laws of physics? In that case, I do get it, and I super don't "It's perfectly compatible with the laws of physics." Then I don't know what you mean. "I mean that there's clearly some experiential stuff accompanying the physical process." I don't know what that means. "Do you have experience or not?" I have internal representations, and I can access them to some degree. It's up to you to tell me if that's experience or not. "Okay, look. You can conceptually separate the information content from how it feels to have that content. Not physically separate them, perhaps, but conceptually. The what-it-feels-like part is qualia. So do you have that or not?" I don't know what that means, so I don't know. As I said, I have internal representations, but I don't think there's anything in addition to those representations, and I'm not sure what that would even mean. and so on. The conversation can also get ugly, with boldface author accusing quotation author of being unscientific and/or quotation author accusing boldface author of being willfully obtuse. On LessWrong, people are arguably pretty good at not talking past each other, but the pattern above still happens. So what's going on? The Two Intuition Clusters The basic model I'm proposing is that core intuitions about consciousness tend to cluster into two camps, with most miscommunication being the result of someone failing to communicate with the other camp. For this post, we'll call the camp of boldface author Camp #1 and the camp of quotation author Camp #2. Characteristics Camp #1 tends to think of consciousness as a non-special high-level phenomenon. Solving consciousness is then tantamount to solving the Meta-Problem of consciousness, which is to explain why we think/claim to have consciousness. In other words, once we've explained why people keep uttering the sounds kon-shush-nuhs, we've explained all the hard observable facts, and the idea that there's anything else seems dangerously speculative/unscientific. No complicated metaphysics is required for this approach. Conversely, Camp #2 is convinced that there is an experience thing that exists in a fundamental way. There's no agreement on what this thing is – theories range anywhere from hardcore physicalist accounts to substance dualists that postulate causally active non-material stuff – but they all agree that there is something that needs explaining. Also, getting your metaphysics right is probably a part of making progress. The camps are ubiquitous; once you have the concept, you will see it everywhere consciousness is discussed. Even single comments often betray allegiance to one camp or the other. Apparent exceptions are usually from people who are well-read on the subject and may have optimized...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some background for reasoning about dual-use alignment research, published by Charlie Steiner on May 18, 2023 on The AI Alignment Forum. This is pretty basic. But I still made a bunch of mistakes when writing this, so maybe it's worth writing. This is background to a specific case I'll put in the next post. It's like a a tech tree If we're looking at the big picture, then whether some piece of research is net positive or net negative isn't an inherent property of that research; it depends on how that research is situated in the research ecosystem that will eventually develop superintelligent AI. Consider this toy game in the picture. We start at the left and can unlock technologies, with unlocks going faster the stronger our connections to prerequisites. The red and yellow technologies in the picture are superintelligent AI - pretend that as soon as one of those technologies is unlocked, the hastiest fraction of AI researchers are immediately going to start building it. Your goal is for humanity to unlock yellow technology before a red one. This game would be trivial if everyone agreed with you. But there are many people doing research, and they have all kinds of motivations - some want as many nodes to be unlocked as possible (pure research - blue), some want to personally unlock a green node (profit - green), some want to unlock the nearest red or yellow node no matter which it is (blind haste - red), and some want the same thing as you (beneficial AI - yellow) but you have a hard time coordinating with them. In this baseline tech tree game, it's pretty easy to play well. If you're strong, just take the shortest path to a yellow node that doesn't pass too close to any red nodes. If you're weak, identify where the dominant paradigm is likely to end up, and do research that differentially advantages yellow nodes in that future. The tech tree is wrinkly But of course there are lots of wrinkles not in the basic tech tree, which can be worth bearing in mind when strategizing about research. Actions in the social and political arenas. You might be motivated to change your research priorities based on how it could change peoples' minds about AI safety, or how it could affect government regulation. Publishing and commercialization. If a player publishes, they get more money and prestige, which boosts their ability to do future research. Other people can build on published research. Not publishing is mainly useful to you if you're already in a position of strength, and don't want to give competitors the chance to outrace you to a nearby red node (and of course profit-motivated players will avoid publishing things that might help competitors beat them to a green node). Uncertainty. We lack exact knowledge of the tech tree, which makes it harder to plan long chains of research in advance. Uncertainty about the tech tree forces us to develop local heuristics - ways to decide what to do based on information close at hand. Uncertainty adds a different reason you might not publish a technology: if you thought it was going to be a good idea to research when you started, but then you learned new things about the tech tree and changed your mind. Inhomogeneities between actors and between technologies. Different organizations are better at researching different technologies - MIRI is not just a small OpenAI. Ultimately, which technologies are the right ones to research depends on your model of the world / how you expect the future to go. Drawing actual tech trees can be a productive exercise for strategy-building, but you might also find it less useful than other ways of strategizing. We're usually mashing together definitions I'd like to win the tech tree game. Let's define a "good" technology as one that would improve our chances of winning if it was unlocked for free, given the st...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some background for reasoning about dual-use alignment research, published by Charlie Steiner on May 18, 2023 on LessWrong. This is pretty basic. But I still made a bunch of mistakes when writing this, so maybe it's worth writing. This is background to a specific case I'll put in the next post. It's like a a tech tree If we're looking at the big picture, then whether some piece of research is net positive or net negative isn't an inherent property of that research; it depends on how that research is situated in the research ecosystem that will eventually develop superintelligent AI. Consider this toy game in the picture. We start at the left and can unlock technologies, with unlocks going faster the stronger our connections to prerequisites. The red and yellow technologies in the picture are superintelligent AI - pretend that as soon as one of those technologies is unlocked, the hastiest fraction of AI researchers are immediately going to start building it. Your goal is for humanity to unlock yellow technology before a red one. This game would be trivial if everyone agreed with you. But there are many people doing research, and they have all kinds of motivations - some want as many nodes to be unlocked as possible (pure research - blue), some want to personally unlock a green node (profit - green), some want to unlock the nearest red or yellow node no matter which it is (blind haste - red), and some want the same thing as you (beneficial AI - yellow) but you have a hard time coordinating with them. In this baseline tech tree game, it's pretty easy to play well. If you're strong, just take the shortest path to a yellow node that doesn't pass too close to any red nodes. If you're weak, identify where the dominant paradigm is likely to end up, and do research that differentially advantages yellow nodes in that future. The tech tree is wrinkly But of course there are lots of wrinkles not in the basic tech tree, which can be worth bearing in mind when strategizing about research. Actions in the social and political arenas. You might be motivated to change your research priorities based on how it could change peoples' minds about AI safety, or how it could affect government regulation. Publishing and commercialization. If a player publishes, they get more money and prestige, which boosts their ability to do future research. Other people can build on published research. Not publishing is mainly useful to you if you're already in a position of strength, and don't want to give competitors the chance to outrace you to a nearby red node (and of course profit-motivated players will avoid publishing things that might help competitors beat them to a green node). Uncertainty. We lack exact knowledge of the tech tree, which makes it harder to plan long chains of research in advance. Uncertainty about the tech tree forces us to develop local heuristics - ways to decide what to do based on information close at hand. Uncertainty adds a different reason you might not publish a technology: if you thought it was going to be a good idea to research when you started, but then you learned new things about the tech tree and changed your mind. Inhomogeneities between actors and between technologies. Different organizations are better at researching different technologies - MIRI is not just a small OpenAI. Ultimately, which technologies are the right ones to research depends on your model of the world / how you expect the future to go. Drawing actual tech trees can be a productive exercise for strategy-building, but you might also find it less useful than other ways of strategizing. We're usually mashing together definitions I'd like to win the tech tree game. Let's define a "good" technology as one that would improve our chances of winning if it was unlocked for free, given the state of the ga...

A special Dodgers clubhouse show hosted by Charlie Steiner and Rick Monday. DV gets all of the player reaction after the Dodgers win their 9th Division title in 10 years.

A special Dodgers clubhouse show hosted by Charlie Steiner and Rick Monday. DV gets all of the player reaction after the Dodgers win their 9th Division title in 10 years.

Tony opens the show by talking about Patrick Reed's $750 million lawsuit, and also about an advertisement he saw that needs to be changed, and he also talks about finding a new brand of ice cream. Steve Sands of the Golf Channel calls in to talk about Cam Smith, Tiger Woods meeting with the top PGA players, and the Patrick Reed lawsuit, Charlie Steiner phones in to catch up with Tony abound he tells the story of how he landed the job he wanted since he was 5 years old, and Tony closes out the show by opening up the Mailbag. Songs : Al Barnes “San Diego” ; “California Punched Me in the Eye” To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Off-day Dodger Talk with David Vassegh recapping the 2022 All-Star Game at Dodger Stadium with Charlie Steiner.