Podcasts about P90

durée : 00:59:04 - Cautionneries - Par La Caution. Embarquement immédiat pour un voyage musical avec Nikkfurie.

In this Patreon episode, man shoots himself while fleeing from police, why take video of your shooting, machine guns are dumb, Jeff wants a P90 but not full auto, American Rifle by Alexander Rose is a great book for gun nerds, Andy and Jeff nerd out on the old American armory system,  now we want black powder cannons and triangular bayonets, Andy wants a pistol suppressor, Silencer Central delivers cans to your door, binary Glock triggers, and much more!  Subscribe on Patreon to get an extra episode every week! Listen on YouTube! Andy on Instagram - andy.e.605 Jeff on Instagram - jeff_the_monster_king MW Aktiv Wear - mw_aktiv_wear Not Another Shooting Show on Reddit

A day in the life of rural Hungary.By FinalStand. Listen to the Podcast at Explicit Novels.'Here be Dragons' wasn't always a tourist gimmick."I didn't say you could have a drink," the Vizsla commented."Oh, my apologies," I shrugged. I put the stein on a nearby table and waited."Have a seat," she directed. I came up to her table and examined the three empty chairs. I held back until she pointed to the chair opposite her. I sat down, but didn't make eye contact. Instead, I examined the various paintings and photographs on the walls. It was an old place."You killed Matthias, even though you knew he worked for me," she uttered."I can confirm that information to be correct," I looked her way. That, wasn't what she expected."Why?""Why what?" I countered. There was a method to my madness; this was going to be a lesson in competence, and what happens when you don't respect it."Why did you kill Matthias?""I needed a reason?" I tried to look pensive. "Maybe I didn't like the cut of his facial hair?""Do you think this is a joke?" she replied dryly. "The Black Hand always avenge our own.""Damn," I looked perplexed. "No one told me that when I arrived. Can we call Matthias's extermination a 50/50 bad call, both ways?""Matthias was my cousin," the Vizsla continued."My condolences," I sighed. "The next Black Hand douche-bag the Amazons waste, I'll have them ask if he's related to you first. How's that?""You are so not likely to have that opportunity," she pointed out."Oh," I laughed, "you are so wrong about that.""You are far stupider than I had been informed," the Vizsla's eyes narrowed."Nope. You and your cast of 'Dumb and Dumber' have been treating us like idiots since we touched down at Ferenc Liszt International, so I'm pretending to be that simpleton sock-puppet just for you, Vizsla. You've added to that by heaping disrespect and derision on my people," I grinned."You tried to have me and my entourage murdered and Matthias paid the price for that. Everyone knows I'm here. And after your bungled attempt to have me killed, no one is going to believe you did anything but murder me, if I don't show up eventually. Now do you prefer the stupid me, or the brighter than normal me?""If you think acting like a smart-ass is somehow endearing, you are mistaken," she let me know."Whatever," I shrugged. "You called this meeting. What do you want?""Beyond killing one of my lieutenants, I wanted to know what you are doing here?" she studied me."I would like to leave now. I'm wasting my time here," I responded."I want answers," she pressed."You have been given the answers to both your talking points, Matthias died because of your orders and I am here looking for three lost Amazon bloodlines," I replied."That seems bizarre," the Vizsla expressed her doubts."Bizarre? You are talking to the sole male Amazon House Head in three thousand years," I reminded her. "Besides, you only just now finished telling me how the Black Hand look after their own. The Amazons are the same way; we have lost kin who need to be made aware of their background.""What do we do about Matthias?" the Vizsla asked."In all honesty, had he not personally threatened to stab a member of my team, I would have settled for kicking the crap out of him. He put a knife to Ms. Martin's throat. That assured his death sentence. I think the Host will be willing to accept my hypothesis that Matthias was acting on his own initiative, which should settle the matter."And just like that, the expediency of the Black Hand shown forth. The truth of the matter was that he had acted on the Vizsla's orders. Unfortunately, that would have meant my side would have come after the Vizsla and she would have had to avenge his death, lots of needless bloodshed. So Matthias posthumously became a rabid dog gone rogue and one who ended up crossing the wrong people. No vengeance required by anyone. We could get back to business."That is settled. So, what do you want from your new allies?" the Vizsla inquired. A certain level of cold-blooded ruthlessness had been required to achieve her spot in the Black Hand. Likewise, honesty was the best policy when dealing with casually lethal people. They didn't like self-important asses wasting their time."I need to find an individual named 'Branko'. He has kidnapped a young lady who is one of our lost Amazons. We don't require any aid, but if you could leave Selena with us, it would be appreciated," I requested."What are you going to do when you catch up with this 'Branko'?" she questioned."I'd like to say I am going to buy her back, but I think we both know that is a pipe-dream. He's not going to like me interfering in his business, so I'm going to kill him, and any other bastards who are in close proximity," I confessed. She studied me for over a minute."Do you wish a piece of advice?" the Vizsla said."Of course," I nodded. It cost me nothing to acknowledge her vastly superior experience."Take a step back," she advised. Seeing that I didn't understand, "If you recall every single death by your hand, you will go mad. You don't possess the detachment of a true killer, Cáel. Not every member of the Black Hand is an assassin.Your driver, Josef, is from a long line of Black Hand members. He doesn't have what it takes to get close and personal in order to kill a human being, so he drives and provides security. He still matters and serves a necessary function." That was almost nice of her. The advice was based on her decision to keep me around as a useful tool. Going nuts would derail that."There is the life we wish to lead, and the life we must lead, Vizsla," I recalled. There was so much there, whirling around in my skull, it took me all this time to find the link I was looking for. Recall every single death by my hand, "On January 26th, 1847, the Black Hand Chapter House of the Wolf in Verona was wiped out, there were no survivors.""If you say so," she regarded me oddly."Yeah, look into it. Then come back to me when you have the right questions," I stood up. "And 'Branko'?""I will relay information on this individual to Selena. We should have something by the time you get back to Buda," she got out before one of the bodyguards came running our way.He had his H and K MP5 out and was in deep conversation with his ear piece."Our two spotters failed to respond correctly," he told the Vizsla in Hungarian. She gave me another quick once over."My people?" I rose slowly.The Vizsla gave the man a subtle hand gesture. Seconds later, pushing Alkonyka ahead of them, Pamela, Selena and Josef came running through the door. Pamela and Selena had our duffels. Two more Black Hand materialized from a back room.The Black Hand was actually a small outfit. Each Chapter had two or three houses, each with four or five true assassins and maybe six times that in support personnel/recruits in each location. That meant the entire Black Hand organization numbered less than 1000. They had several thousand peripheral contacts across their sphere of Europe and they could purchase some sort of private security given time. But their best protection was their hidden nature and small size. That also meant what we had was what we had. There was no Black Hand SWAT team on the way.Working with hand gestures alone, the Vizsla was directing us to a trap door behind the bar. Josef's phone rang. He hesitantly answered."It is for you," he offered it to our host. She took it. Halfway through the caller's diatribe, she shot me a suspicious look."Why don't you ask him?" she stated, then handed me the phone."Hello Nyilas. Do you know who this is?" the man on the other end stated, in Mycenean Greek."Yes, I do. What do you want? I'm kind of busy here?" I grinned. It was laughing at death all over again."I can relieve you of your pressing schedule. You and the other Amazon step outside and I'll make it quick.""No can-do Studly," I smirked. "If I go out there, it is going to take a while.""I sincerely doubt that.""Don't sell yourself short," I jibed. "I figure clipping off those bull-sized testicles of yours is going to take some work. But I do promise that after I make you a eunuch, I'll use a condom when I bend you over and make you my bitch too. Was there anything else you wanted to know?""No. I think we have a mutual understanding," he laughed. "I'll be seeing you soon." He hung up."Who was that?" Vizsla inquired. She wasn't alone in her curiosity."Ajax," I beamed confidence. I was confident my tenure on this Earth was ending real soon."I think we should be leaving," Vizsla suggested."Selena, help Alkonyka get her sister back," I requested. "I'll catch up when I can. Pamela, you do what you feel you need to do. Vizsla, they are after me, so I'm going to keep them busy while you get away," I explained.No useless 'you don't have to do this' nonsense. She knew the score, I wasn't a member of her outfit and she wanted to live. She did do me one favor. She gave another hand movement. Selena slit Josef's throat in a surprise motion.He didn't die right away. Selena's slash made bleeding out inevitable, but he'd be a while in dying. Odds were, that only Vizsla and Josef knew in advance where we were meeting. Whatever payoff the Condottieri had put in his bank account wasn't going to do him any good. Selena bent over his still-thrashing body and removed his pistol."I will bring you Angyalka Lovasz," Selena pledged. Pamela and I were gearing up. Ajax and his buddies were going to be coming for me any second now. Alkonyka gave me one more worried look before she vanished into the secret basement. "Don't be late," was the last thing Selena said before going down into the darkness. Pamela made sure the trap door was covered up.Lust and Bullets"We've used Butch and Sundance," Pamela checked her L42 Enfield Sniper Rifle. It was the weapon Pamela had trained with and used for longer than I'd been alive, old yet very effective even today."Heat?" I offered up. "You can be De Niro and I can be Kilmer.""Nice. Michael Mann really had a way of killing people," Pamela grinned, then pumped her eyebrows. "Too bad I end up dead in this one.""We'll avoid airports, you should be safe," I joked. Three explosions rocked the building, shooting glass throughout the place. Fortunately, Pamela and I were hiding behind the bar."Let's go," she whispered over the din. Charging out the front door seemed pretty suicidal to me, but Pamela's copious battle lore was something I had the utmost faith in. I respected her judgment and followed along. There was a method to her madness. Two 40 mm grenades had taken out the two cars parked in front. A third launched grenade had blown open the door.The petrol in the cars equated to flaming wreckage and a huge smoke screen. It was broad daylight, no night vision goggles. The flames made IR useless and the smoke temporarily obscured regular vision. The machineguns going off around us scared the crap out of me. It was my old buddy, suppression fire: they weren't shooting directly at us.Metaphysically, Ishara was dueling with Ares. There was a low stone wall, a little over a meter high, that separated an adjacent field from the inn's gravel parking lot. Right as we got to our side of it, three of Ajax's boys came up on the other. Pamela and I remained perfectly still, crouching tightly against our shelter.Two knelt and fired several bursts from their H and K HK416 (Wow! Germany's newest killing machine, they looked slick) into the closest open windows while the third one fired a grenade in. Again, we remained perfectly still. We were about two meters from those three. The drab color of our hastily donned dusters, the congested air and our stillness combined to save us from their notice.The second after that grenade went off, the three vaulted the wall and rushed the building. From the cacophony of the battle, they were storming the building from several directions at once."Quick, go find that guy with the machinegun," Pamela whispered over a feral grin. How was I going to do that?The old fashioned way, I leapt over the wall and ran away from all the flames, explosions and the continuous widespread fusillade of assault weapons fire. I was partially bent over as I ran. I'm still a big guy though. The machine gunner was in a shallow dip in the meadow 30 meters away, on the edge of the woods.He saw me, shifted his MG4 (fuck Ajax and his crew for having the best Bang-Bangs) minutely and unleashed hell my way. In hindsight, the 1st round flattened against my duster as it impacted my upper left thigh. Round #2 hit the duster again, coming below my vest, but hitting my belt (every bit of leather helps).The #3 556 mm slug hit my vest due south of my belly button (Fuck!), # 4 landed a few centimeters up and to the right, taking in both the duster and my ballistic vest. The #5 round clipped my lower side of my right ribcage. The resulting force sent me spinning back and to my right.Honestly, as I landed hard on my back (no rolling with the blow this time), I thought a midget mule team had kicked me in the guts. Apparently, I made a convincing mortally wounded human being. He stopped shooting and Pamela got pissed.I learned a few things at that moment: you do not get used to being shot; you can never appreciate the value of good body amour enough; you can never understand the true value of a sniper until your life is totally in their hands; and damn, Pamela was exceptional. Pamela put a bullet through his nasal cavity in that split second between him exposing himself with his muzzle flashes and deciding to put a few more bullets into my prone form.Pain dictated that I lie where I was. Survival instincts overrode that. I went to my side, pushed up and resumed my crouched stance. Then I was running once more until I could throw myself beside his corpse. I was stunningly calm. Machineguns, snipers, I had to cover Pamela's run across the meadow. I didn't stay by the dead gunner.I grabbed his weapon, some spare ammo and quick-stepped it to the wood line. I rapidly assessed the best spot that could provide cover from each flank. That was where I went down, cradled the device and started shooting at any muzzle flash I could see. The moment I opened fire, Pamela began her own sprint.Unlike my mad dash, Pamela took evasive maneuvers, serpentine, which worked out well when one sniper figured out she wasn't one of them. He/she had two shots at her before she dove past me. Her mien was one of intense, emptiness? She gave me a quick pat-down to make sure I wasn't gushing blood, took a deep breath and then smirked."Come on, Dummy!" she laughed. "We still have a shot at a sequel.""Shot, sequel, you are a laugh riot," I wheezed as I stood, abandoned the MG4 and joined her as we both ran deeper into the woods. A few shots zinged past us before Ajax's crew realized we were in full-on flight mode. They weren't going to waste the bullets.This was the point where archaic and modern warfare diverged. In the olden (pre-Pamela, ow! How did she know what I was thinking?) days, when your enemy broke and ran, it was relatively easy to run them down and slaughter them in their panic. If a few men tried to stem the tide, they would be quickly overwhelmed.After the invention of rapid-fire rifles, that changed. Suddenly, headlong pursuit could be incredibly costly. All it took was a small, resolute band to find some sort of hard cover and they could buy minutes, or even hours, for their retreating brethren. Sure, if you were willing to pay the butcher's bill, you could storm their position.But you had to understand, each defender could fire and work the bolt action in under three seconds. You reloaded your magazine with a prepared clip ~ maybe five more seconds. Ten men could put 150 bullets down range per minute as long as their ammo held out. Sending men into that kind of firepower was murder; very few troops could sustain their attack under those conditions.Ajax's resurrected Mycenaean's were tough enough to do it. Ajax's problem was their finite number. Despite catching Ajax off-guard with Pamela's mad plan, her ungodly skills and a great deal of my pain, we had only managed to kill one so far. The great unknowns were terrain (we didn't know where we were,) and my luck.As Pamela and I ran through the forest at a good clip, we began to make out a specific background noise. It was a river. Not a creek, stream, waterfall, or dam, a river."Did you pack your jet ski?" Pamela snorted."I left it in the car. You said it was so '1990's'," I panted back. A few more footsteps and,

143 - Phil X In episode 143 of “Have Guitar Will Travel”, presented by Vintage Guitar Magazine, host, James Patrick Regan speaks with guitarist extraordinaire Phil X. In their conversation Phil tells us about living in LA, his childhood in Toronto and his early musical experiences being encouraged to play guitar by his father who played Bouzouki. Phil tells about the bands he's played in: Aldo Nova, Triumph, Powder and of course Bon Jovi as well as his own band Phil X and the Drills. Phil talks gear throughout the years including his signature pickups from Arcane and his signature guitars including his new Gibson SG a body style he loves. He also tells us about how worked in his father's restaurant to pay for his gear growing up. Phil also tells us his love of the P90 pickup. Phil discusses his studio work playing on a lot of the American Idol stars work (Kelly Clarkson, Daughtry) as well as Tommy Lee's solo work, Rob Zombie and Alice Cooper. You can find a comprehensive list of his session work on Phil's fan site: philxfanclub.com Phil tells us how he became a vocalist and how he developed his range… he sings the high part of “Living On A Prayer” with Bon Jovi live. Phil talks about “Fretted Americana” a YouTube channel showcasing guitars. We talk a little about NAMM and the places he'll be during the convention as well as gigs coming up. Phil is active on the socials, his website is down right now, but he suggested his fan site is the place to find info: philxfanclub.com . . Please subscribe, like, comment, share and review this podcast! . #VintageGuitarMagazine #PhilX #AldoNova #GibsonGuitar #GibsonCustomShop #BonJovi #ArcanePickups #Triumph #GuitarHero #Shredder #theDeadlies #Powder #PhilXandtheDrills #haveguitarwilltravelpodcast #hgwt #HGWT . . . Please like, comment, and share this podcast! Download Link

Dr. Tony Leachon, a public health reform advocate, explains everything that's wrong with transferring close to P90 billion from the Philippine Health Insurance Corp.

Editor's note: One of the top reasons we have hundreds of companies and thousands of AI Engineers joining the World's Fair next week is, apart from discussing technology and being present for the big launches planned, to hire and be hired! Listeners loved our previous Elicit episode and were so glad to welcome 2 more members of Elicit back for a guest post (and bonus podcast) on how they think through hiring. Don't miss their AI engineer job description, and template which you can use to create your own hiring plan! How to Hire AI EngineersJames Brady, Head of Engineering @ Elicit (ex Spring, Square, Trigger.io, IBM)Adam Wiggins, Internal Journalist @ Elicit (Cofounder Ink & Switch and Heroku)If you're leading a team that uses AI in your product in some way, you probably need to hire AI engineers. As defined in this article, that's someone with conventional engineering skills in addition to knowledge of language models and prompt engineering, without being a full-fledged Machine Learning expert.But how do you hire someone with this skillset? At Elicit we've been applying machine learning to reasoning tools since 2018, and our technical team is a mix of ML experts and what we can now call AI engineers. This article will cover our process from job description through interviewing. (You can also flip the perspectives here and use it just as easily for how to get hired as an AI engineer!)My own journeyBefore getting into the brass tacks, I want to share my journey to becoming an AI engineer.Up until a few years ago, I was happily working my job as an engineering manager of a big team at a late-stage startup. Like many, I was tracking the rapid increase in AI capabilities stemming from the deep learning revolution, but it was the release of GPT-3 in 2020 which was the watershed moment. At the time, we were all blown away by how the model could string together coherent sentences on demand. (Oh how far we've come since then!)I'd been a professional software engineer for nearly 15 years—enough to have experienced one or two technology cycles—but I could see this was something categorically new. I found this simultaneously exciting and somewhat disconcerting. I knew I wanted to dive into this world, but it seemed like the only path was going back to school for a master's degree in Machine Learning. I started talking with my boss about options for taking a sabbatical or doing a part-time distance learning degree.In 2021, I instead decided to launch a startup focused on productizing new research ideas on ML interpretability. It was through that process that I reached out to Andreas—a leading ML researcher and founder of Elicit—to see if he would be an advisor. Over the next few months, I learned more about Elicit: that they were trying to apply these fascinating technologies to the real-world problems of science, and with a business model that aligned it with safety goals. I realized that I was way more excited about Elicit than I was about my own startup ideas, and wrote about my motivations at the time.Three years later, it's clear this was a seismic shift in my career on the scale of when I chose to leave my comfy engineering job at IBM to go through the Y Combinator program back in 2008. Working with this new breed of technology has been more intellectually stimulating, challenging, and rewarding than I could have imagined.Deep ML expertise not requiredIt's important to note that AI engineers are not ML experts, nor is that their best contribution to a tech team.In our article Living documents as an AI UX pattern, we wrote:It's easy to think that AI advancements are all about training and applying new models, and certainly this is a huge part of our work in the ML team at Elicit. But those of us working in the UX part of the team believe that we have a big contribution to make in how AI is applied to end-user problems.We think of LLMs as a new medium to work with, one that we've barely begun to grasp the contours of. New computing mediums like GUIs in the 1980s, web/cloud in the 90s and 2000s, and multitouch smartphones in the 2000s/2010s opened a whole new era of engineering and design practices. So too will LLMs open new frontiers for our work in the coming decade.To compare to the early era of mobile development: great iOS developers didn't require a detailed understanding of the physics of capacitive touchscreens. But they did need to know the capabilities and limitations of a multi-touch screen, the constrained CPU and storage available, the context in which the user is using it (very different from a webpage or desktop computer), etc.In the same way, an AI engineer needs to work with LLMs as a medium that is fundamentally different from other compute mediums. That means an interest in the ML side of things, whether through their own self-study, tinkering with prompts and model fine-tuning, or following along in #llm-paper-club. But this understanding is so that they can work with the medium effectively versus, say, spending their days training new models.Language models as a chaotic mediumSo if we're not expecting deep ML expertise from AI engineers, what are we expecting? This brings us to what makes LLMs different.We'll assume already that our ideal candidate is already inspired by, and full of ideas about, all the new capabilities AI can bring to software products. But the flip side is all the things that make this new medium difficult to work with. LLM calls are annoying due to high latency (measured in tens of seconds sometimes, rather than milliseconds), extreme variance on latency, high error rates even under normal operation. Not to mention getting extremely different answers to the same prompt provided to the same model on two subsequent calls!The net effect is that an AI engineer, even working at the application development level, needs to have a skillset comparable to distributed systems engineering. Handling errors, retries, asynchronous calls, streaming responses, parallelizing and recombining model calls, the halting problem, and fallbacks are just some of the day-in-the-life of an AI engineer. Chaos engineering gets new life in the era of AI.Skills and qualities in candidatesLet's put together what we don't need (deep ML expertise) with what we do (work with capabilities and limitations of the medium). Thus we start to see what Elicit looks for in AI engineers:* Conventional software engineering skills. Especially back-end engineering on complex, data-intensive applications.* Professional, real-world experience with applications at scale.* Deep, hands-on experience across a few back-end web frameworks.* Light devops and an understanding of infrastructure best practices.* Queues, message buses, event-driven and serverless architectures, … there's no single “correct” approach, but having a deep toolbox to draw from is very important.* A genuine curiosity and enthusiasm for the capabilities of language models.* One or more serious projects (side projects are fine) of using them in interesting ways on a unique domain.* …ideally with some level of factored cognition, e.g. breaking the problem down into chunks, making thoughtful decisions about which things to push to the language model and which stay within the realm of conventional heuristics and compute capabilities.* Personal studying with resources like Elicit's ML reading list. Part of the role is collaborating with the ML engineers and researchers on our team. To do so, the candidate needs to “speak their language” somewhat, just as a mobile engineer needs some familiarity with backends in order to collaborate effectively on API creation with backend engineers.* An understanding of the challenges that come along with working with large models (high latency, variance, etc.) leading to a defensive, fault-first mindset.* Careful and principled handling of error cases, asynchronous code (and ability to reason about and debug it), streaming data, caching, logging and analytics for understanding behavior in production.* This is a similar mindset that one can develop working on conventional apps which are complex, data-intensive, or large-scale apps. The difference is that an AI engineer will need this mindset even when working on relatively small scales!On net, a great AI engineer will combine two seemingly contrasting perspectives: knowledge of, and a sense of wonder for, the capabilities of modern ML models; but also the understanding that this is a difficult and imperfect foundation, and the willingness to build resilient and performant systems on top of it.Here's the resulting AI engineer job description for Elicit. And here's a template that you can borrow from for writing your own JD.Hiring processOnce you know what you're looking for in an AI engineer, the process is not too different from other technical roles. Here's how we do it, broken down into two stages: sourcing and interviewing.SourcingWe're primarily looking for people with (1) a familiarity with and interest in ML, and (2) proven experience building complex systems using web technologies. The former is important for culture fit and as an indication that the candidate will be able to do some light prompt engineering as part of their role. The latter is important because language model APIs are built on top of web standards and—as noted above—aren't always the easiest tools to work with.Only a handful of people have built complex ML-first apps, but fortunately the two qualities listed above are relatively independent. Perhaps they've proven (2) through their professional experience and have some side projects which demonstrate (1).Talking of side projects, evidence of creative and original prototypes is a huge plus as we're evaluating candidates. We've barely scratched the surface of what's possible to build with LLMs—even the current generation of models—so candidates who have been willing to dive into crazy “I wonder if it's possible to…” ideas have a huge advantage.InterviewingThe hard skills we spend most of our time evaluating during our interview process are in the “building complex systems using web technologies” side of things. We will be checking that the candidate is familiar with asynchronous programming, defensive coding, distributed systems concepts and tools, and display an ability to think about scaling and performance. They needn't have 10+ years of experience doing this stuff: even junior candidates can display an aptitude and thirst for learning which gives us confidence they'll be successful tackling the difficult technical challenges we'll put in front of them.One anti-pattern—something which makes my heart sink when I hear it from candidates—is that they have no familiarity with ML, but claim that they're excited to learn about it. The amount of free and easily-accessible resources available is incredible, so a motivated candidate should have already dived into self-study.Putting all that together, here's the interview process that we follow for AI engineer candidates:* 30-minute introductory conversation. Non-technical, explaining the interview process, answering questions, understanding the candidate's career path and goals.* 60-minute technical interview. This is a coding exercise, where we play product manager and the candidate is making changes to a little web app. Here are some examples of topics we might hit upon through that exercise:* Update API endpoints to include extra metadata. Think about appropriate data types. Stub out frontend code to accept the new data.* Convert a synchronous REST API to an asynchronous streaming endpoint.* Cancellation of asynchronous work when a user closes their tab.* Choose an appropriate data structure to represent the pending, active, and completed ML work which is required to service a user request.* 60–90 minute non-technical interview. Walk through the candidate's professional experience, identifying high and low points, getting a grasp of what kinds of challenges and environments they thrive in.* On-site interviews. Half a day in our office in Oakland, meeting as much of the team as possible: more technical and non-technical conversations.The frontier is wide openAlthough Elicit is perhaps further along than other companies on AI engineering, we also acknowledge that this is a brand-new field whose shape and qualities are only just now starting to form. We're looking forward to hearing how other companies do this and being part of the conversation as the role evolves.We're excited for the AI Engineer World's Fair as another next step for this emerging subfield. And of course, check out the Elicit careers page if you're interested in joining our team.Podcast versionTimestamps* [00:00:24] Intros* [00:05:25] Defining the Hiring Process* [00:08:42] Defensive AI Engineering as a chaotic medium* [00:10:26] Tech Choices for Defensive AI Engineering* [00:14:04] How do you Interview for Defensive AI Engineering* [00:19:25] Does Model Shadowing Work?* [00:22:29] Is it too early to standardize Tech stacks?* [00:32:02] Capabilities: Offensive AI Engineering* [00:37:24] AI Engineering Required Knowledge* [00:40:13] ML First Mindset* [00:45:13] AI Engineers and Creativity* [00:47:51] Inside of Me There Are Two Wolves* [00:49:58] Sourcing AI Engineers* [00:58:45] Parting ThoughtsTranscript[00:00:00] swyx: Okay, so welcome to the Latent Space Podcast. This is another remote episode that we're recording. This is the first one that we're doing around a guest post. And I'm very honored to have two of the authors of the post with me, James and Adam from Elicit. Welcome, James. Welcome, Adam.[00:00:22] James Brady: Thank you. Great to be here.[00:00:23] Hey there.[00:00:24] Intros[00:00:24] swyx: Okay, so I think I will do this kind of in order. I think James, you're, you're sort of the primary author. So James, you are head of engineering at Elicit. You also, We're VP Eng at Teespring and Spring as well. And you also , you have a long history in sort of engineering. How did you, , find your way into something like Elicit where, , it's, you, you are basically traditional sort of VP Eng, VP technology type person moving into a more of an AI role.[00:00:53] James Brady: Yeah, that's right. It definitely was something of a Sideways move if not a left turn. So the story there was I'd been doing, as you said, VP technology, CTO type stuff for around about 15 years or so, and Notice that there was this crazy explosion of capability and interesting stuff happening within AI and ML and language models, that kind of thing.[00:01:16] I guess this was in 2019 or so, and decided that I needed to get involved. , this is a kind of generational shift. And Spent maybe a year or so trying to get up to speed on the state of the art, reading papers, reading books, practicing things, that kind of stuff. Was going to found a startup actually in in the space of interpretability and transparency, and through that met Andreas, who has obviously been on the, on the podcast before asked him to be an advisor for my startup, and he countered with, maybe you'd like to come and run the engineering team at Elicit, which it turns out was a much better idea.[00:01:48] And yeah, I kind of quickly changed in that direction. So I think some of the stuff that we're going to be talking about today is how actually a lot of the work when you're building applications with AI and ML looks and smells and feels much more like conventional software engineering with a few key differences rather than really deep ML stuff.[00:02:07] And I think that's one of the reasons why I was able to transfer skills over from one place to the other.[00:02:12] swyx: Yeah, I[00:02:12] James Brady: definitely[00:02:12] swyx: agree with that. I, I do often say that I think AI engineering is about 90 percent software engineering with like the, the 10 percent of like really strong really differentiated AI engineering.[00:02:22] And that might, that obviously that number might change over time. I want to also welcome Adam onto my podcast because you welcomed me onto your podcast two years ago.[00:02:31] Adam Wiggins: Yeah, that was a wonderful episode.[00:02:32] swyx: That was, that was a fun episode. You famously founded Heroku. You just wrapped up a few years working on Muse.[00:02:38] And now you've described yourself as a journalist, internal journalist working on Elicit.[00:02:43] Adam Wiggins: Yeah, well I'm kind of a little bit in a wandering phase here and trying to take this time in between ventures to see what's out there in the world and some of my wandering took me to the Elicit team. And found that they were some of the folks who were doing the most interesting, really deep work in terms of taking the capabilities of language models and applying them to what I feel like are really important problems.[00:03:08] So in this case, science and literature search and, and, and that sort of thing. It fits into my general interest in tools and productivity software. I, I think of it as a tool for thought in many ways, but a tool for science, obviously, if we can accelerate that discovery of new medicines and things like that, that's, that's just so powerful.[00:03:24] But to me, it's a. It's kind of also an opportunity to learn at the feet of some real masters in this space, people who have been working on it since it was, before it was cool, if you want to put it that way. So for me, the last couple of months have been this crash course, and why I sometimes describe myself as an internal journalist is I'm helping to write some, some posts, including Supporting James in this article here we're doing for latent space where I'm just bringing my writing skill and that sort of thing to bear on their very deep domain expertise around language models and applying them to the real world and kind of surface that in a way that's I don't know, accessible, legible, that, that sort of thing.[00:04:03] And so, and the great benefit to me is I get to learn this stuff in a way that I don't think I would, or I haven't, just kind of tinkering with my own side projects.[00:04:12] swyx: I forgot to mention that you also run Ink and Switch, which is one of the leading research labs, in my mind, of the tools for thought productivity space, , whatever people mentioned there, or maybe future of programming even, a little bit of that.[00:04:24] As well. I think you guys definitely started the local first wave. I think there was just the first conference that you guys held. I don't know if you were personally involved.[00:04:31] Adam Wiggins: Yeah, I was one of the co organizers along with a few other folks for, yeah, called Local First Conf here in Berlin.[00:04:36] Huge success from my, my point of view. Local first, obviously, a whole other topic we can talk about on another day. I think there actually is a lot more what would you call it , handshake emoji between kind of language models and the local first data model. And that was part of the topic of the conference here, but yeah, topic for another day.[00:04:55] swyx: Not necessarily. I mean , I, I selected as one of my keynotes, Justine Tunney, working at LlamaFall in Mozilla, because I think there's a lot of people interested in that stuff. But we can, we can focus on the headline topic. And just to not bury the lead, which is we're talking about hire, how to hire AI engineers, this is something that I've been looking for a credible source on for months.[00:05:14] People keep asking me for my opinions. I don't feel qualified to give an opinion and it's not like I have. So that's kind of defined hiring process that I'm super happy with, even though I've worked with a number of AI engineers.[00:05:25] Defining the Hiring Process[00:05:25] swyx: I'll just leave it open to you, James. How was your process of defining your hiring, hiring roles?[00:05:31] James Brady: Yeah. So I think the first thing to say is that we've effectively been hiring for this kind of a role since before you, before you coined the term and tried to kind of build this understanding of what it was.[00:05:42] So, which is not a bad thing. Like it's, it was a, it was a good thing. A concept, a concept that was coming to the fore and effectively needed a name, which is which is what you did. So the reason I mentioned that is I think it was something that we kind of backed into, if you will. We didn't sit down and come up with a brand new role from, from scratch of this is a completely novel set of responsibilities and skills that this person would need.[00:06:06] However, it is a A kind of particular blend of different skills and attitudes and and curiosities interests, which I think makes sense to kind of bundle together. So in the, in the post, the three things that we say are most important for a highly effective AI engineer are first of all, conventional software engineering skills, which is Kind of a given, but definitely worth mentioning.[00:06:30] The second thing is a curiosity and enthusiasm for machine learning and maybe in particular language models. That's certainly true in our case. And then the third thing is to do with basically a fault first mindset, being able to build systems that can handle things going wrong in, in, in some sense.[00:06:49] And yeah, the I think the kind of middle point, the curiosity about ML and language models is probably fairly self evident. They're going to be working with, and prompting, and dealing with the responses from these models, so that's clearly relevant. The last point, though, maybe takes the most explaining.[00:07:07] To do with this fault first mindset and the ability to, to build resilient systems. The reason that is, is so important is because compared to normal APIs, where normal, think of something like a Stripe API or a search API or something like this. The latency when you're working with language models is, is wild, like you can get 10x variation.[00:07:32] I mean, I was looking at the stats before, actually, before, before the podcast. We do often, normally, in fact, see a 10x variation in the P90 latency over the course of, Half an hour, an hour when we're prompting these models, which is way higher than if you're working with a, more kind of conventional conventionally backed API.[00:07:49] And the responses that you get, the actual content and the responses are naturally unpredictable as well. They come back with different formats. Maybe you're expecting JSON. It's not quite JSON. You have to handle this stuff. And also the, the semantics of the messages are unpredictable too, which is, which is a good thing.[00:08:08] Like this is one of the things that you're looking for from these language models, but it all adds up to needing to. Build a resilient, reliable, solid feeling system on top of this fundamentally, well, certainly currently fundamentally shaky foundation. The models do not behave in the way that you would like them to.[00:08:28] And yeah, the ability to structure the code around them such that it does give the user this warm, reassuring, Snappy, solid feeling is is really what we're driving for there.[00:08:42] Defensive AI Engineering as a chaotic medium[00:08:42] Adam Wiggins: What really struck me as we, we dug in on the content for this article was that third point there. The, the language models is this kind of chaotic medium, this, this dragon, this wild horse you're, you're, you're riding and trying to guide in the direction that is going to be useful and reliable to users, because I think.[00:08:58] So much of software engineering is about making things not only high performance and snappy, but really just making it stable, reliable, predictable, which is literally the opposite of what you get from from the language models. And yet, yeah, the output is so useful, and indeed, some of their Creativity, if you want to call it that, which is, is precisely their value.[00:09:19] And so you need to work with this medium. And I guess the nuanced or the thing that came out of Elissa's experience that I thought was so interesting is quite a lot of working with that is things that come from distributed systems engineering. But you have really the AI engineers as we're defining them or, or labeling them on the illicit team is people who are really application developers.[00:09:39] You're building things for end users. You're thinking about, okay, I need to populate this interface with some response to user input. That's useful to the tasks they're trying to do, but you have this. This is the thing, this medium that you're working with that in some ways you need to apply some of this chaos engineering, distributed systems engineering, which typically those people with those engineering skills are not kind of the application level developers with the product mindset or whatever, they're more deep in the guts of a, of a system.[00:10:07] And so it's, those, those skills and, and knowledge do exist throughout the engineering discipline, but sort of putting them together into one person that is That feels like sort of a unique thing and working with the folks on the Elicit team who have that skills I'm quite struck by that unique that unique blend.[00:10:23] I haven't really seen that before in my 30 year career in technology.[00:10:26] Tech Choices for Defensive AI Engineering[00:10:26] swyx: Yeah, that's a Fascinating I like the reference to chaos engineering. I have some appreciation, I think when you had me on your podcast, I was still working at Temporal and that was like a nice Framework, if you live within Temporal's boundaries, you can pretend that all those faults don't exist, and you can, you can code in a sort of very fault tolerant way.[00:10:47] What is, what is you guys solutions around this, actually? Like, I think you're, you're emphasizing having the mindset, but maybe naming some technologies would help? Not saying that you have to adopt these technologies, but they're just, they're just quick vectors into what you're talking about when you're, when you're talking about distributed systems.[00:11:03] Like, that's such a big, chunky word, , like are we talking, are Kubernetes or, and I suspect we're not, , like we're, we're talking something else now.[00:11:10] James Brady: Yeah, that's right. It's more at the application level rather than at the infrastructure level, at least, at least the way that it works for us.[00:11:17] So there's nothing kind of radically novel here. It is more a careful application of existing concepts. So the kinds of tools that we reach for to handle these kind of slightly chaotic objects that Adam was just talking about, are retries and fallbacks and timeouts and careful error handling. And, yeah, the standard stuff, really.[00:11:39] There's also a great degree of dependence. We rely heavily on parallelization because, , these language models are not innately very snappy, and , there's just a lot of I. O. going back and forth. So All these things I'm talking about when I was in my earlier stages of a career, these are kind of the things that are the difficult parts that most senior software engineers will be better at.[00:12:01] It is careful error handling, and concurrency, and fallbacks, and distributed systems, and, , eventual consistency, and all this kind of stuff and As Adam was saying, the kind of person that is deep in the guts of some kind of distributed systems, a really high, high scale backend kind of a problem would probably naturally have these kinds of skills.[00:12:21] But you'll find them on, on day one, if you're building a, , an ML powered app, even if it's not got massive scale. I think one one thing that I would mention that we do do yeah, maybe, maybe two related things, actually. The first is we're big fans of strong typing. We share the types all the way from the Backend Python code all the way to the to the front end in TypeScript and find that is I mean We'd probably do this anyway But it really helps one reason around the shapes of the data which can going to be going back and forth and that's really important When you can't rely upon You you're going to have to coerce the data that you get back from the ML if you want if you want for it to be structured basically speaking and The second thing which is related is we use checked exceptions inside our Python code base, which means that we can use the type system to make sure we are handling, properly handling, all of the, the various things that could be going wrong, all the different exceptions that could be getting raised.[00:13:16] So, checked exceptions are not, not really particularly popular. Actually there's not many people that are big fans of them. For our particular use case, to really make sure that we've not just forgotten to handle, , This particular type of error we have found them useful to to, to force us to think about all the different edge cases that can come up.[00:13:32] swyx: Fascinating. How just a quick note of technology. How do you share types from Python to TypeScript? Do you, do you use GraphQL? Do you use something[00:13:39] James Brady: else? We don't, we don't use GraphQL. Yeah. So we've got the We've got the types defined in Python, that's the source of truth. And we go from the OpenAPI spec, and there's a, there's a tool that you work and use to generate types dynamically, like TypeScript types from those OpenAPI definitions.[00:13:57] swyx: Okay, excellent. Okay, cool. Sorry, sorry for diving into that rabbit hole a little bit. I always like to spell out technologies for people to dig their teeth into.[00:14:04] How do you Interview for Defensive AI Engineering[00:14:04] swyx: One thing I'll, one thing I'll mention quickly is that a lot of the stuff that you mentioned is typically not part of the normal interview loop.[00:14:10] It's actually really hard to interview for because this is the stuff that you polish out in, as you go into production, the coding interviews are typically about the happy path. How do we do that? How do we, how do we design, how do you look for a defensive fault first mindset?[00:14:24] Because you can defensive code all day long and not add functionality. to your to your application.[00:14:29] James Brady: Yeah, it's a great question and I think that's exactly true. Normally the interview is about the happy path and then there's maybe a box checking exercise at the end of the candidate says of course in reality I would handle the edge cases or something like this and that unfortunately isn't isn't quite good enough when when the happy path is is very very narrow and yeah there's lots of weirdness on either side so basically speaking, it's just a case of, of foregrounding those kind of concerns through the interview process.[00:14:58] It's, there's, there's no magic to it. We, we talk about this in the, in the po in the post that we're gonna be putting up on, on Laton space. The, there's two main technical exercises that we do through our interview process for this role. The first is more coding focus, and the second is more system designy.[00:15:16] Yeah. White whiteboarding a potential solution. And in, without giving too much away in the coding exercise. You do need to think about edge cases. You do need to think about errors. The exercise consists of adding features and fixing bugs inside the code base. And in both of those two cases, it does demand, because of the way that we set the application up and the interview up, it does demand that you think about something other than the happy path.[00:15:41] But your thinking is the right prompt of how do we get the candidate thinking outside of the, the kind of normal Sweet spot, smooth smooth, smoothly paved path. In terms of the system design interview, that's a little easier to prompt this kind of fault first mindset because it's very easy in that situation just to say, let's imagine that, , this node dies, how does the app still work?[00:16:03] Let's imagine that this network is, is going super slow. Let's imagine that, I don't know, like you, you run out of, you run out of capacity in, in, in this database that you've sketched out here, how do you handle that, that, that sort of stuff. So. It's, in both cases, they're not firmly anchored to and built specifically around language models and ways language models can go wrong, but we do exercise the same muscles of thinking defensively and yeah, foregrounding the edge cases, basically.[00:16:32] Adam Wiggins: James, earlier there you mentioned retries. And this is something that I think I've seen some interesting debates internally about things regarding, first of all, retries are, can be costly, right? In general, this medium, in addition to having this incredibly high variance and response rate, and, , being non deterministic, is actually quite expensive.[00:16:50] And so, in many cases, doing a retry when you get a fail does make sense, but actually that has an impact on cost. And so there is Some sense to which, at least I've seen the AI engineers on our team, worry about that. They worry about, okay, how do we give the best user experience, but balance that against what the infrastructure is going to, , is going to cost our company, which I think is again, an interesting mix of, yeah, again, it's a little bit the distributed system mindset, but it's also a product perspective and you're thinking about the end user experience, but also the.[00:17:22] The bottom line for the business, you're bringing together a lot of a lot of qualities there. And there's also the fallback case, which is kind of, kind of a related or adjacent one. I think there was also a discussion on that internally where, I think it maybe was search, there was something recently where there was one of the frontline search providers was having some, yeah, slowness and outages, and essentially then we had a fallback, but essentially that gave people for a while, especially new users that come in that don't the difference, they're getting a They're getting worse results for their search.[00:17:52] And so then you have this debate about, okay, there's sort of what is correct to do from an engineering perspective, but then there's also what actually is the best result for the user. Is giving them a kind of a worse answer to their search result better, or is it better to kind of give them an error and be like, yeah, sorry, it's not working right at the moment, try again.[00:18:12] Later, both are obviously non optimal, but but this is the kind of thing I think that that you run into or, or the kind of thing we need to grapple with a lot more than you would other kinds of, of mediums.[00:18:24] James Brady: Yeah, that's a really good example. I think it brings to the fore the two different things that you could be optimizing for of uptime and response at all costs on one end of the spectrum and then effectively fragility, but kind of, if you get a response, it's the best response we can come up with at the other end of the spectrum.[00:18:43] And where you want to land there kind of depends on, well, it certainly depends on the app, obviously depends on the user. I think it depends on the, feature within the app as well. So in the search case that you, that you mentioned there, in retrospect, we probably didn't want to have the fallback. And we've actually just recently on Monday, changed that to Show an error message rather than giving people a kind of degraded experience in other situations We could use for example a large language model from a large language model from provider B rather than provider A and Get something which is within the A few percentage points performance, and that's just a really different situation.[00:19:21] So yeah, like any interesting question, the answer is, it depends.[00:19:25] Does Model Shadowing Work?[00:19:25] swyx: I do hear a lot of people suggesting I, let's call this model shadowing as a defensive technique, which is, if OpenAI happens to be down, which, , happens more often than people think then you fall back to anthropic or something.[00:19:38] How realistic is that, right? Like you, don't you have to develop completely different prompts for different models and won't the, won't the performance of your application suffer from whatever reason, right? Like it may be caused differently or it's not maintained in the same way. I, I think that people raise this idea of fallbacks to models, but I don't think it's, I don't, I don't see it practiced very much.[00:20:02] James Brady: Yeah, it is, you, you definitely need to have a different prompt if you want to stay within a few percentage points degradation Like I, like I said before, and that certainly comes at a cost, like fallbacks and backups and things like this It's really easy for them to go stale and kind of flake out on you because they're off the beaten track And In our particular case inside of Elicit, we do have fallbacks for a number of kind of crucial functions where it's going to be very obvious if something has gone wrong, but we don't have fallbacks in all cases.[00:20:40] It really depends on a task to task basis throughout the app. So I can't give you a kind of a, a single kind of simple rule of thumb for, in this case, do this. And in the other, do that. But yeah, we've it's a little bit easier now that the APIs between the anthropic models and opening are more similar than they used to be.[00:20:59] So we don't have two totally separate code paths with different protocols, like wire protocols to, to speak, which makes things easier, but you're right. You do need to have different prompts if you want to, have similar performance across the providers.[00:21:12] Adam Wiggins: I'll also note, just observing again as a relative newcomer here, I was surprised, impressed, not sure what the word is for it, at the blend of different backends that the team is using.[00:21:24] And so there's many The product presents as kind of one single interface, but there's actually several dozen kind of main paths. There's like, for example, the search versus a data extraction of a certain type, versus chat with papers, versus And each one of these, , the team has worked very hard to pick the right Model for the job and craft the prompt there, but also is constantly testing new ones.[00:21:48] So a new one comes out from either, from the big providers or in some cases, Our own models that are , running on, on essentially our own infrastructure. And sometimes that's more about cost or performance, but the point is kind of switching very fluidly between them and, and very quickly because this field is moving so fast and there's new ones to choose from all the time is like part of the day to day, I would say.[00:22:11] So it isn't more of a like, there's a main one, it's been kind of the same for a year, there's a fallback, but it's got cobwebs on it. It's more like which model and which prompt is changing weekly. And so I think it's quite, quite reasonable to to, to, to have a fallback that you can expect might work.[00:22:29] Is it too early to standardize Tech stacks?[00:22:29] swyx: I'm curious because you guys have had experience working at both, , Elicit, which is a smaller operation and, and larger companies. A lot of companies are looking at this with a certain amount of trepidation as, as, , it's very chaotic. When you have, when you have , one engineering team that, that, knows everyone else's names and like, , they, they, they, they meet constantly in Slack and knows what's going on.[00:22:50] It's easier to, to sync on technology choices. When you have a hundred teams, all shipping AI products and all making their own independent tech choices. It can be, it can be very hard to control. One solution I'm hearing from like the sales forces of the worlds and Walmarts of the world is that they are creating their own AI gateway, right?[00:23:05] Internal AI gateway. This is the one model hub that controls all the things and has our standards. Is that a feasible thing? Is that something that you would want? Is that something you have and you're working towards? What are your thoughts on this stuff? Like, Centralization of control or like an AI platform internally.[00:23:22] James Brady: Certainly for larger organizations and organizations that are doing things which maybe are running into HIPAA compliance or other, um, legislative tools like that. It could make a lot of sense. Yeah. I think for the TLDR for something like Elicit is we are small enough, as you indicated, and need to have full control over all the levers available and switch between different models and different prompts and whatnot, as Adam was just saying, that that kind of thing wouldn't work for us.[00:23:52] But yeah, I've spoken with and, um, advised a couple of companies that are trying to sell into that kind of a space or at a larger stage, and it does seem to make a lot of sense for them. So, for example, if you're trying to sell If you're looking to sell to a large enterprise and they cannot have any data leaving the EU, then you need to be really careful about someone just accidentally putting in, , the sort of US East 1 GPT 4 endpoints or something like this.[00:24:22] I'd be interested in understanding better what the specific problem is that they're looking to solve with that, whether it is to do with data security or centralization of billing, or if they have a kind of Suite of prompts or something like this that people can choose from so they don't need to reinvent the wheel again and again I wouldn't be able to say without understanding the problems and their proposed solutions , which kind of situations that be better or worse fit for but yeah for illicit where really the The secret sauce, if there is a secret sauce, is which models we're using, how we're using them, how we're combining them, how we're thinking about the user problem, how we're thinking about all these pieces coming together.[00:25:02] You really need to have all of the affordances available to you to be able to experiment with things and iterate rapidly. And generally speaking, whenever you put these kind of layers of abstraction and control and generalization in there, that, that gets in the way. So, so for us, it would not work.[00:25:19] Adam Wiggins: Do you feel like there's always a tendency to want to reach for standardization and abstractions pretty early in a new technology cycle?[00:25:26] There's something comforting there, or you feel like you can see them, or whatever. I feel like there's some of that discussion around lang chain right now. But yeah, this is not only so early, but also moving so fast. , I think it's . I think it's tough to, to ask for that. That's, that's not the, that's not the space we're in, but the, yeah, the larger an organization, the more that's your, your default is to, to, to want to reach for that.[00:25:48] It, it, it's a sort of comfort.[00:25:51] swyx: Yeah, I find it interesting that you would say that , being a founder of Heroku where , you were one of the first platforms as a service that more or less standardized what, , that sort of early developer experience should have looked like.[00:26:04] And I think basically people are feeling the differences between calling various model lab APIs and having an actual AI platform where. , all, all their development needs are thought of for them. , it's, it's very much, and, and I, I defined this in my AI engineer post as well.[00:26:19] Like the model labs just see their job ending at serving models and that's about it. But actually the responsibility of the AI engineer has to fill in a lot of the gaps beyond that. So.[00:26:31] Adam Wiggins: Yeah, that's true. I think, , a huge part of the exercise with Heroku, which It was largely inspired by Rails, which itself was one of the first frameworks to standardize the SQL database.[00:26:42] And people had been building apps like that for many, many years. I had built many apps. I had made my own templates based on that. I think others had done it. And Rails came along at the right moment. We had been doing it long enough that you see the patterns and then you can say look let's let's extract those into a framework that's going to make it not only easier to build for the experts but for people who are relatively new the best practices are encoded into you.[00:27:07] That framework, , Model View Controller, to take one example. But then, yeah, once you see that, and once you experience the power of a framework, and again, it's so comforting, and you can develop faster, and it's easier to onboard new people to it because you have these standards. And this consistency, then folks want that for something new that's evolving.[00:27:29] Now here I'm thinking maybe if you fast forward a little to, for example, when React came on the on the scene, , a decade ago or whatever. And then, okay, we need to do state management. What's that? And then there's, , there's a new library every six months. Okay, this is the one, this is the gold standard.[00:27:42] And then, , six months later, that's deprecated. Because of course, it's evolving, you need to figure it out, like the tacit knowledge and the experience of putting it in practice and seeing what those real What those real needs are are, are critical, and so it's, it is really about finding the right time to say yes, we can generalize, we can make standards and abstractions, whether it's for a company, whether it's for, , a library, an open source library, for a whole class of apps and it, it's very much a, much more of a A judgment call slash just a sense of taste or , experience to be able to say, Yeah, we're at the right point.[00:28:16] We can standardize this. But it's at least my, my very, again, and I'm so new to that, this world compared to you both, but my, my sense is, yeah, still the wild west. That's what makes it so exciting and feels kind of too early for too much. too much in the way of standardized abstractions. Not that it's not interesting to try, but , you can't necessarily get there in the same way Rails did until you've got that decade of experience of whatever building different classes of apps in that, with that technology.[00:28:45] James Brady: Yeah, it's, it's interesting to think about what is going to stay more static and what is expected to change over the coming five years, let's say. Which seems like when I think about it through an ML lens, it's an incredibly long time. And if you just said five years, it doesn't seem, doesn't seem that long.[00:29:01] I think that, that kind of talks to part of the problem here is that things that are moving are moving incredibly quickly. I would expect, this is my, my hot take rather than some kind of official carefully thought out position, but my hot take would be something like the You can, you'll be able to get to good quality apps without doing really careful prompt engineering.[00:29:21] I don't think that prompt engineering is going to be a kind of durable differential skill that people will, will hold. I do think that, The way that you set up the ML problem to kind of ask the right questions, if you see what I mean, rather than the specific phrasing of exactly how you're doing chain of thought or few shot or something in the prompt I think the way that you set it up is, is probably going to be remain to be trickier for longer.[00:29:47] And I think some of the operational challenges that we've been talking about of wild variations in, in, in latency, And handling the, I mean, one way to think about these models is the first lesson that you learn when, when you're an engineer, software engineer, is that you need to sanitize user input, right?[00:30:05] It was, I think it was the top OWASP security threat for a while. Like you, you have to sanitize and validate user input. And we got used to that. And it kind of feels like this is the, The shell around the app and then everything else inside you're kind of in control of and you can grasp and you can debug, etc.[00:30:22] And what we've effectively done is, through some kind of weird rearguard action, we've now got these slightly chaotic things. I think of them more as complex adaptive systems, which , related but a bit different. Definitely have some of the same dynamics. We've, we've injected these into the foundations of the, of the app and you kind of now need to think with this defined defensive mindset downwards as well as upwards if you, if you see what I mean.[00:30:46] So I think it would gonna, it's, I think it will take a while for us to truly wrap our heads around that. And also these kinds of problems where you have to handle things being unreliable and slow sometimes and whatever else, even if it doesn't happen very often, there isn't some kind of industry wide accepted way of handling that at massive scale.[00:31:10] There are definitely patterns and anti patterns and tools and whatnot, but it's not like this is a solved problem. So I would expect that it's not going to go down easily as a, as a solvable problem at the ML scale either.[00:31:23] swyx: Yeah, excellent. I would describe in, in the terminology of the stuff that I've written in the past, I describe this inversion of architecture as sort of LLM at the core versus LLM or code at the core.[00:31:34] We're very used to code at the core. Actually, we can scale that very well. When we build LLM core apps, we have to realize that the, the central part of our app that's orchestrating things is actually prompt, prone to, , prompt injections and non determinism and all that, all that good stuff.[00:31:48] I, I did want to move the conversation a little bit from the sort of defensive side of things to the more offensive or, , the fun side of things, capabilities side of things, because that is the other part. of the job description that we kind of skimmed over. So I'll, I'll repeat what you said earlier.[00:32:02] Capabilities: Offensive AI Engineering[00:32:02] swyx: It's, you want people to have a genuine curiosity and enthusiasm for the capabilities of language models. We just, we're recording this the day after Anthropic just dropped Cloud 3. 5. And I was wondering, , maybe this is a good, good exercise is how do people have Curiosity and enthusiasm for capabilities language models when for example the research paper for cloud 3.[00:32:22] 5 is four pages[00:32:23] James Brady: Maybe that's not a bad thing actually in this particular case So yeah If you really want to know exactly how the sausage was made That hasn't been possible for a few years now in fact for for these new models but from our perspective as when we're building illicit What we primarily care about is what can these models do?[00:32:41] How do they perform on the tasks that we already have set up and the evaluations we have in mind? And then on a slightly more expansive note, what kinds of new capabilities do they seem to have? Can we elicit, no pun intended, from the models? For example, well, there's, there's very obvious ones like multimodality , there wasn't that and then there was that, or it could be something a bit more subtle, like it seems to be getting better at reasoning, or it seems to be getting better at metacognition, or Or it seems to be getting better at marking its own work and giving calibrated confidence estimates, things like this.[00:33:19] So yeah, there's, there's plenty to be excited about there. It's just that yeah, there's rightly or wrongly been this, this, this shift over the last few years to not give all the details. So no, but from application development perspective we, every time there's a new model release, there's a flow of activity in our Slack, and we try to figure out what's going on.[00:33:38] What it can do, what it can't do, run our evaluation frameworks, and yeah, it's always an exciting, happy day.[00:33:44] Adam Wiggins: Yeah, from my perspective, what I'm seeing from the folks on the team is, first of all, just awareness of the new stuff that's coming out, so that's, , an enthusiasm for the space and following along, and then being able to very quickly, partially that's having Slack to do this, but be able to quickly map that to, okay, What does this do for our specific case?[00:34:07] And that, the simple version of that is, let's run the evaluation framework, which Lissa has quite a comprehensive one. I'm actually working on an article on that right now, which I'm very excited about, because it's a very interesting world of things. But basically, you can just try, not just, but try the new model in the evaluations framework.[00:34:27] Run it. It has a whole slew of benchmarks, which includes not just Accuracy and confidence, but also things like performance, cost, and so on. And all of these things may trade off against each other. Maybe it's actually, it's very slightly worse, but it's way faster and way cheaper, so actually this might be a net win, for example.[00:34:46] Or, it's way more accurate. But that comes at its slower and higher cost, and so now you need to think about those trade offs. And so to me, coming back to the qualities of an AI engineer, especially when you're trying to hire for them, It's this, it's, it is very much an application developer in the sense of a product mindset of What are our users or our customers trying to do?[00:35:08] What problem do they need solved? Or what what does our product solve for them? And how does the capabilities of a particular model potentially solve that better for them than what exists today? And by the way, what exists today is becoming an increasingly gigantic cornucopia of things, right? And so, You say, okay, this new model has these capabilities, therefore, , the simple version of that is plug it into our existing evaluations and just look at that and see if it, it seems like it's better for a straight out swap out, but when you talk about, for example, you have multimodal capabilities, and then you say, okay, wait a minute, actually, maybe there's a new feature or a whole new There's a whole bunch of ways we could be using it, not just a simple model swap out, but actually a different thing we could do that we couldn't do before that would have been too slow, or too inaccurate, or something like that, that now we do have the capability to do.[00:35:58] I think of that as being a great thing. I don't even know if I want to call it a skill, maybe it's even like an attitude or a perspective, which is a desire to both be excited about the new technology, , the new models and things as they come along, but also holding in the mind, what does our product do?[00:36:16] Who is our user? And how can we connect the capabilities of this technology to how we're helping people in whatever it is our product does?[00:36:25] James Brady: Yeah, I'm just looking at one of our internal Slack channels where we talk about things like new new model releases and that kind of thing And it is notable looking through these the kind of things that people are excited about and not It's, I don't know the context, the context window is much larger, or it's, look at how many parameters it has, or something like this.[00:36:44] It's always framed in terms of maybe this could be applied to that kind of part of Elicit, or maybe this would open up this new possibility for Elicit. And, as Adam was saying, yeah, I don't think it's really a I don't think it's a novel or separate skill, it's the kind of attitude I would like to have all engineers to have at a company our stage, actually.[00:37:05] And maybe more generally, even, which is not just kind of getting nerd sniped by some kind of technology number, fancy metric or something, but how is this actually going to be applicable to the thing Which matters in the end. How is this going to help users? How is this going to help move things forward strategically?[00:37:23] That kind of, that kind of thing.[00:37:24] AI Engineering Required Knowledge[00:37:24] swyx: Yeah, applying what , I think, is, is, is the key here. Getting hands on as well. I would, I would recommend a few resources for people listening along. The first is Elicit's ML reading list, which I, I found so delightful after talking with Andreas about it.[00:37:38] It looks like that's part of your onboarding. We've actually set up an asynchronous paper club instead of my discord for people following on that reading list. I love that you separate things out into tier one and two and three, and that gives people a factored cognition way of Looking into the, the, the corpus, right?[00:37:55] Like yes, the, the corpus of things to know is growing and the water is slowly rising as far as what a bar for a competent AI engineer is. But I think, , having some structured thought as to what are the big ones that everyone must know I think is, is, is key. It's something I, I haven't really defined for people and I'm, I'm glad that this is actually has something out there that people can refer to.[00:38:15] Yeah, I wouldn't necessarily like make it required for like the job. Interview maybe, but , it'd be interesting to see like, what would be a red flag. If some AI engineer would not know, I don't know what, , I don't know where we would stoop to, to call something required knowledge, , or you're not part of the cool kids club.[00:38:33] But there increasingly is something like that, right? Like, not knowing what context is, is a black mark, in my opinion, right?[00:38:40] I think it, I think it does connect back to what we were saying before of this genuine Curiosity about and that. Well, maybe it's, maybe it's actually that combined with something else, which is really important, which is a self starting bias towards action, kind of a mindset, which again, everybody needs.[00:38:56] Exactly. Yeah. Everyone needs that. So if you put those two together, or if I'm truly curious about this and I'm going to kind of figure out how to make things happen, then you end up with people. Reading, reading lists, reading papers, doing side projects, this kind of, this kind of thing. So it isn't something that we explicitly included.[00:39:14] We don't have a, we don't have an ML focused interview for the AI engineer role at all, actually. It doesn't really seem helpful. The skills which we are checking for, as I mentioned before, this kind of fault first mindset. And conventional software engineering kind of thing. It's, it's 0. 1 and 0.[00:39:32] 3 on the list that, that we talked about. In terms of checking for ML curiosity and there are, how familiar they are with these concepts. That's more through talking interviews and culture fit types of things. We want for them to have a take on what Elisa is doing. doing, certainly as they progress through the interview process.[00:39:50] They don't need to be completely up to date on everything we've ever done on day zero. Although, , that's always nice when it happens. But for them to really engage with it, ask interesting questions, and be kind of bought into our view on how we want ML to proceed. I think that is really important, and that would reveal that they have this kind of this interest, this ML curiosity.[00:40:13] ML First Mindset[00:40:13] swyx: There's a second aspect to that. I don't know if now's the right time to talk about it, which is, I do think that an ML first approach to building software is something of a different mindset. I could, I could describe that a bit now if that, if that seems good, but yeah, I'm a team. Okay. So yeah, I think when I joined Elicit, this was the biggest adjustment that I had to make personally.[00:40:37] So as I said before, I'd been, Effectively building conventional software stuff for 15 years or so, something like this, well, for longer actually, but professionally for like 15 years. And had a lot of pattern matching built into my brain and kind of muscle memory for if you see this kind of problem, then you do that kind of a thing.[00:40:56] And I had to unlearn quite a lot of that when joining Elicit because we truly are ML first and try to use ML to the fullest. And some of the things that that means is, This relinquishing of control almost, at some point you are calling into this fairly opaque black box thing and hoping it does the right thing and dealing with the stuff that it sends back to you.[00:41:17] And that's very different if you're interacting with, again, APIs and databases, that kind of a, that kind of a thing. You can't just keep on debugging. At some point you hit this, this obscure wall. And I think the second, the second part to this is the pattern I was used to is that. The external parts of the app are where most of the messiness is, not necessarily in terms of code, but in terms of degrees of freedom, almost.[00:41:44] If the user can and will do anything at any point, and they'll put all sorts of wonky stuff inside of text inputs, and they'll click buttons you didn't expect them to click, and all this kind of thing. But then by the time you're down into your SQL queries, for example, as long as you've done your input validation, things are pretty pretty well defined.[00:42:01] And that, as we said before, is not really the case. When you're working with language models, there is this kind of intrinsic uncertainty when you get down to the, to the kernel, down to the core. Even, even beyond that, there's all that stuff is somewhat defensive and these are things to be wary of to some degree.[00:42:18] Though the flip side of that, the really kind of positive part of taking an ML first mindset when you're building applications is that you, If you, once you get comfortable taking your hands off the wheel at a certain point and relinquishing control, letting go then really kind of unexpected powerful things can happen if you lean on the, if you lean on the capabilities of the model without trying to overly constrain and slice and dice problems with to the point where you're not really wringing out the most capability from the model that you, that you might.[00:42:47] So, I was trying to think of examples of this earlier, and one that came to mind was we were working really early when just after I joined Elicit, we were working on something where we wanted to generate text and include citations embedded within it. So it'd have a claim, and then a, , square brackets, one, in superscript, something, something like this.[00:43:07] And. Every fiber in my, in my, in my being was screaming that we should have some way of kind of forcing this to happen or Structured output such that we could guarantee that this citation was always going to be present later on that the kind of the indication of a footnote would actually match up with the footnote itself and Kind of went into this symbolic.[00:43:28] I need full control kind of kind of mindset and it was notable that Andreas Who's our CEO, again, has been on the podcast, was was the opposite. He was just kind of, give it a couple of examples and it'll probably be fine. And then we can kind of figure out with a regular expression at the end. And it really did not sit well with me, to be honest.[00:43:46] I was like, but it could say anything. I could say, it could literally say anything. And I don't know about just using a regex to sort of handle this. This is a potent feature of the app. But , this is that was my first kind of, , The starkest introduction to this ML first mindset, I suppose, which Andreas has been cultivating for much longer than me, much longer than most, of yeah, there might be some surprises of stuff you get back from the model, but you can also It's about finding the sweet spot, I suppose, where you don't want to give a completely open ended prompt to the model and expect it to do exactly the right thing.[00:44:25] You can ask it too much and it gets confused and starts repeating itself or goes around in loops or just goes off in a random direction or something like this. But you can also over constrain the model. And not really make the most of the, of the capabilities. And I think that is a mindset adjustment that most people who are coming into AI engineering afresh would need to make of yeah, giving up control and expecting that there's going to be a little bit of kind of extra pain and defensive stuff on the tail end, but the benefits that you get as a, as a result are really striking.[00:44:58] The ML first mindset, I think, is something that I struggle with as well, because the errors, when they do happen, are bad. , they will hallucinate, and your systems will not catch it sometimes if you don't have large enough of a sample set.[00:45:13] AI Engineers and Creativity[00:45:13] swyx: I'll leave it open to you, Adam. What else do you think about when you think about curiosity and exploring capabilities?[00:45:22] Do people are there reliable ways to get people to push themselves? for joining us on Capabilities, because I think a lot of times we have this implicit overconfidence, maybe, of we think we know what it is, what a thing is, when actually we don't, and we need to keep a more open mind, and I think you do a particularly good job of Always having an open mind, and I want to get that out of more engineers that I talk to, but I, I, I, I struggle sometimes.[00:45:45] Adam Wiggins: I suppose being an engineer is, at its heart, this sort of contradiction of, on one hand, yeah,

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: Let's Fund: Impact of our $1M crowdfunded grant to the Center for Clean Energy Innovation, published by Hauke Hillebrandt on April 4, 2024 on The Effective Altruism Forum. Let's Fund researches pressing problems, like climate change, and then crowdfunds for nonprofits working on effective policy solutions. One such policy is clean energy innovation (e.g. via more grant funding for scientists to invent better solar panels). Making clean energy cheaper has many benefits because it reduces: Emissions Energy poverty Air pollution (which kills millions a year) Revenue for autocratic petrostates[1] Extreme climate risks (since if countries agreements to reduce emissions like Paris were to break down, cheaper clean energy hedges against this[2]) Since 2019, we've crowdfunded $1M for the Center for Clean Energy Innovation (CCEI) at ITIF, a non-profit think tank in DC. One example of our grantees work is researching the effects of higher and smarter clean energy R&D spending and communicating the results to policy-makers. Our research showed that this is the most effective climate policy[3] and was featured on Vox (which Bill Gates retweeted![4]). As a result, ~2000 donors crowdfunded a $1M+ for CCEI to do more think tank work (e.g. do research, talk to policy-makers, etc.). Here I show how with our grant, CCEI might have e.g. shifted >$100M from less effective clean energy deployment (e.g. subsidies) to more neglected and effective clean energy R&D. The donations might avert a ton CO for less than $0.10. That a leading think tank can cause such shifts becomes plausible, if we look at the pivotal ('hingey') timeline of a political climate so favorable that climate budgets went up by an unprecedented scale: 2020: Big Government Dems win the presidency, house and a razor-thin margin senate majority. Then a CCEI researcher gets a job advising Biden's climate envoy, John Kerry, who had endorsed and blurbed CCEI's Energizing America report and which has been called 'a very influential report', and advice for Biden on how to reform the energy innovation system.[5] 2021: COVID leads to a massive stimulus that includes ~$42B for clean energy RD&D, doubling the yearly budget- an ~$10B increase: [6] This US leadership led 16 countries to pledge ~$100B for the Clean Energy Technologies Demonstration Challenge recently. These increases were politically tractable thanks to tens of thousands of climate activists raising awareness worldwide. But CCEI is part of a much smaller coalition of only hundreds of key movers and shakers (others are: CATF, Carbon180, etc.[7]) that improved the quality of these spending increases by channeling them towards energy RD&D, which is ~10x more effective at ~$10/tC than deployment at ~$100/tC averted (more). Also, our $1M grant was ~2% of donations to US climate governance and a respectable 0.2% to all US think tanks.[8],[9],[10] Based on this, if we assume CCEI caused ~.1-10%[11] of the $10B-100B clean energy RD&D increases - then, our Monte Carlo model (see UseCarlo.com) suggests that CCEI averts ~.5Gt at ~$.002/tC:[12] Distribution p0 p10 p50 p90 UseCarlo.com output Notes / Source Energy R&D budget increase Metalog $0K $10B $42B $100B ~50Gt P10: US increases / y. P50: total stimulus. P90: global agreement CCEI's effect of shifting deploy$ to RD&D$ Metalog 0% 0.1% 2% 10% ~5% Guesstimate: CCEI is part of the coalition of key movers and shakers that shifted budget increases to energy RD&D RD&D effectiveness Metalog $0 $3 $13 $41 ~$20/tC Review on the cost-effectiveness of energy R&D Deployment effectiveness Metalog $0 $0.1K $0.5K $1K ~$500/tC Levelized Cost of Carbon Abatement tC averted via R&D shift Output ~0.5Gt tC averted by R&D- Counterfactual tC averted by deployment Let's Fund grant ~$1M CCEI effectiveness ~$0.002/tC Donor effectiveness ~$0.02/tC Most...

Vi pratar om men även lyssnar på skillnaden mellan PAF-mickar och P90's. Fölster har örat mot marken och berättar om vad som händer i gitarrvärlden. I veckans pryl testar vi Sadist Fuzz från Square Wave Bd. I detta avsnitt: Gibson, UA, Fender, Jakobsson, Square Wave Bd.

This is the second part of the Matador in Eddy County Deal Evaluation.Because of the enormous requests from investors evaluating oil and gas, we are starting a new series showing people how to assess oil and gas M&A or invest. Accredited investors, family offices, and E&P operators are our largest market, asking for these evaluation pieces of training.We want your feedback and recommendations for deals.Reach out to Stu and Michael at https://energynewsbeat.co/ to get your deal reviewed.Highlights of the Podcast00:20 - Divided into two parts, focusing on the Matador deal.00:45 - Explanation of setting up a new type curve for Wolfcamp A.01:08 - Understanding production curves normalized to time zero.09:15 - Discussion on the distribution of EURs (P10, P50, P90).14:21 - Incorporating strip pricing and natural gas liquids (NGL) data.16:37 - Creating individual forecasts for specific wells.19:30 - Incorporating production taxes and ownership interests.20:47 - Analyze cash flows and calculate the internal rate of return (IRR).22:02 - Determining the potential acquisition cost and assessing deal value.A shout-out to our sponsors! WellDatabase and ComboCurve.*We do not offer investment advice; you must contact your tax professional to get the appropriate tax information for your investments. This is only for educational purposes.

Fredrik och Ulf gör ett stortest på Ron Ellis populäraste mikrofoner. Fölster fördjupar sig i ämnet P90 mikrofoner. I veckans pryl pratar vi om StringJoy-strängar. I denna vecka: Ron Ellis, Gibson, Asher, Björk, Fender, Hamel, Stuart, UA, Benson, Hudson, Collings, Gretsch, String Joy, John Pearse.

In this episode, I look at the history and build options in P90 picks that are in one of their peaking popularity cycles.

Zathras warning: LOTS of Star Trek in the beginning of this one. Like, nearly 10 minutes. The management apologizes.The Devil You Know: The theme of this episode is "who does the protecting, and who do they choose to protect." Where the hell did Shaw hide a P90 in a cosmetics counter? ELIAS! You know a goon is done for when you finally learn his name. Fusco kicks butt. Elias may be a moral monster, but the rest of the Machine Team basically is too.The Cold War: It's the meme episode! Tweet us your favorite use of the assassin-chain format. There is a specific mayo to mustard ratio. Greer backstory--he was borrowed from a John Le Carre novel and well on his way to becoming a Bond villain. Nice pastebin reference. The war in heaven continues. Connect with the show at @babylonpodjectHelp us keep the lights on via our Patreon!Justen can be found at @justenwritesAna can be found at @The_Mianaai, and also made our show art.Both Ana and Justen can also be found on The Compleat Discography, a Discworld re-read podcast.Jude Vais can be found at @eremiticjude. His other work can be found at Athrabeth - a Tolkien Podcast and at Garbage of the Five Rings.Clips from the original show remain copyrighted by their original rightsholders, and are used under the Fair Use doctrine.Music is by Arne Parrott, who can be found at http://atptunes.com/This show is edited and produced by Aaron Olson, who can be found at @urizenxvii

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.02.03.527024v1?rss=1 Authors: Lanjewar, A. L., Levitt, P., Eagleson, K. L. Abstract: Cognitive impairment is a common phenotype of neurodevelopmental disorders, but how these deficits arise remains elusive. Determining the onset of discrete cognitive capabilities facilitates studies in probing mechanisms underlying their emergence. The present study analyzed the emergence of contextual fear memory persistence (7-day memory retention) and remote memory (30-day memory retention). There was a rapid transition from postnatal day (P) 20 to P21, in which memory persistence emerged in C57Bl/6J male and female mice. Remote memory was present at P23, but expression was not robust compared to pubertal and adult mice. To address a potential molecular mechanism, the present study examined the MET receptor tyrosine kinase (MET), which when deleted results in fear memory deficits in adult mice and regulates timing of critical period in the visual cortex, positioning it as a regulator for onset of contextual fear memory. Sustaining Met past the normal window of peak cortical expression or deleting Met did not alter the timing of emergence of persistence or remote memory capabilities. However, failure to exhibit fear memory occurred by P90 in mice with reduction or deletion of Met. Remarkably, the number of FOS-expressing infragranular neurons in medial prefrontal cortex (mPFC) did not increase with contextual conditioning at P35 but exhibited enhanced activation at P90. Additionally, MET-expressing neurons were preferentially recruited at P90 compared to P35 during fear memory expression. The studies demonstrate a developmental profile of contextual fear memory capabilities. Further, developmental disruption of Met leads to a delayed functional deficit that arises in adulthood. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Daniel, Ben and Tanya talk about the Science Fiction phenomenon Stargate SG-1 (1997-2007). Based on the film of the same name released in 1994, SG-1 picks us shortly after and expands the story and Universe greatly. Our hosts will discuss their favorite episodes, characters, villains, and a whole lot more of what made SG-1 "POP" for them. Included are excerpts from their interviews with Stargate stars Suanne Braun (Hathor) and Colin Cunningham (Major Paul Davis) who recall what it was like acting on the series, the people who made their marks on them. and their appreciation of what they believe to be the best fans there are; Stargate fans. They answer fan questions and share some laughs with our hosts.So, don your BDU's, Tac Vest, and boots, grab your P90 and get ready to jump through the gate with Popped!MUSICPopped Theme: Spooky-Funk-Instrumental (Royalty Free Artist Unknown needs credit)Background Music: Intro B/G: WatR Double Overhead by ItsWatREpisode B/G:  Lost by DanyDoryNeptune: Holst Performed by the USAF Heritage of America BandHonor and Sword: Daddy s Music Support the show

Today, Catherine is joined by George Lucan of Angus Energy to discuss the company's recent good news around their newly online onshore gas field. We are back online and what a journey, the long-suffering shareholders being rewarded at last, with more to come. Finally, here we are, supply chain crises, an assembled plant, fully automated, what an achievement, almost all our suppliers are British, a great team effort. Right now we are not even scratching the surface, gas production will rise. Major appointments to the board “sidetrack/second compressor to come online” stable flow rates, (P90 resources) sitting on 300m therms, Sidetrack/spudding set for mid-Oct Saltfleetby is putting gas directly into the National Angus Energy, an independent offshore oil and gas company, is focused on developing its UK portfolio of assets. This includes the iconic project Saltfleetby (Lincolnshire), which now delivers gas to the National Grid. Angus Energy is a tale of hard work and success. George Lucan, CEO of Angus Energy, inherited several different oil licenses in the Weald. He then transformed the company's fortunes when he bought 51% of Saltfleetby which was once Britain's most productive offshore gas field. George raised the money over three years to bring Salfleetby to production. Now, in September 2022 Saltfleetby has started putting gas into National Grid. Angus is about to begin receiving regular revenue streams that will provide a foundation for future growth. https://www.share-talk.com/george-lucan-chief-executive-of-angus-energy-aimangs-video-update/

This week, Nathan gets technical! Print, Shoot, Repeat returns alongside renowned 3D firearm Developer Ivan the Troll! The lads get right into Ivan's introduction to printing Austrian lowers, making Twitter accounts out of a dire need to shitpost mag dump videos at ignorant pro and anti-gunners skeptical of 3D firearm reliability, Ivan explains the lore behind the meme of 'It'll blow your hands off!', Nathan touches on the assassination of former Japanese Prime Minister Shinzo Abe and the lads discuss the conversation around DIY arms and how they are almost always immediately conflated with printed ones in the modern news cycle. Also: A rant about how the P90 was almost certainly designed by cokeheads and the weird history behind PDW anti-armor rounds, how Ivan went from making fun of the the .22 TCM round to ‘Stanning' it, the gang talks about anonymity in the 3D printing world and the moronic opinion that being anonymous makes you ‘less of a man', Ivan talks AK and RPK builds, the PPK and 3011, FN Herstal vs FN USA issues, manufacturers and much much more! Links mentioned in this episode: Check out Print Shoot Repeat on Instagram here! Check out Print Shoot Repeat's YouTube channel here! Check out Ivan on YouTube here! Check out our Patreon here to support what we do and get insider perks! Follow the lads on IG: https://www.instagram.com/cbrnart/?hl=en Follow the lads on Twitter: https://twitter.com/CBRNDad Check out our sponsors: Use code: ARTANDWAR10 for $10 off an SMU Belt at AWSin.com Use code: ARTANDWAR for 5% off at midwestgunworks.com Check out our link tree for the rest of our stuff!

Episode 108 features an interview with the supremely talented Matt Artinger of Artinger Guitars. Matt shares with us some stories on how he got started with some early encouragement from Chris Martin or Martin Guitars. We also get into what elements make a good guitar including guitar woods and pickup talk!   Show Links: We also talk about the new Gatekeeper H90 Humbucker sized P90 release. Check those out here: https://www.porterpickups.com/gkp-h90/ Find out about Matts Guitars here: http://www.artingerguitar.com Fill Out The Pickup Chooser Form Here: https://www.porterpickups.com/home/pickup-chooser/   

Hi friends - we know, we know, we're a day late; your buds took a little holiday so we're getting this week's episode out to you on a Tuesday instead of Monday. Please forgive us.That said - a handful of instruments were auctioned recently and we got to thinking: what are the most expensive guitars ever sold? Hang out until the main topic this week and you'll find out! Spoiler: it's mostly 3 brands.Also discussed: Monserrat stories, Dave at the Jackhammer, Drake losing money, big Reverb updates, Rush docs, shimming the vintage 330's bridge P90, eBay woes, Oeksound Soothe update, Gibson teaming up with Guitarwrist, new Universal Audio amp pedals, and Electronic Audio Experiments' update on the Dude Incredible.Hope everyone (in the States) had a positive Memorial Day.

In this third episode of the JLS Show, JMac, Lowney and Stuki select their Top 3 favourite tracks from the Guntz March playlist (with a twist).Additionally they talk P90's, Lowney's vinyl addiction, musical cliches, a certain band's aesthetic and JMac's favourite proverbs. They also delve into some old buried treasures and Stuki makes an apology, of sorts.The March playlist on Spotify: https://open.spotify.com/playlist/2iOOF6hk8rWQtyi0ZEDK1T?si=c72352a5fbae4a68Your Favourite Band Sucks podcast: https://podcasts.apple.com/gb/podcast/your-favorite-band-sucks/id1322283290Transmitter Cranium on YouTube: https://youtu.be/q13NRoG6mvs P90 pickups: https://en.wikipedia.org/wiki/P-90The Sparks Brothers on Netflix: https://www.netflix.com/gb/title/81436982?s=i&trkid=13747225&vlang=en&clip=81508956King Gizzard & The Lizard Wizard Omnium Gatherum article: https://www.guitarworld.com/news/king-gizzard-omnium-gatherum-the-dripping-tapSmashy and Nicey on YouTube: https://youtu.be/IaQCr4PIsHE JMac's harmonica playlist on Spotify: https://open.spotify.com/playlist/3sOKqvaeG4JWvLSTjcDx83?si=8d3f13ea34d7401d Hosted on Acast. See acast.com/privacy for more information.

Welcome to another episode with P90 and the conversations of Gaming, Comics and Nerd Culture

Welcome to another episode with your guy P90

The Costco Kirkland Signature 10 hearing aids offer the most extraordinary value of any raw device on the market, though they are slightly offset by anecdotal reports of inconsistent professional services. In terms of the hearing aid itself, this is an exceptional device for the price of $1400. The Signature 10 is a white-labeled Phonak Paradise P90 RT, which is listed as the top overall hearing aid on the market elsewhere on this list and in our “Best of 2022” YouTube video. It is a phenomenal all-around device, with a natural and clear sound quality in various environments, and all the most important features (specifically a rechargeable battery, Bluetooth for streaming, and a smartphone app). The trial period is 180 days, the longest available on the market, and the warranty is a respectable 2 years for loss and 3 years for repair. If you purchased the P90 in a traditional clinic, you could pay up to 500% more than the Costco price. However, it is a mistake to judge the Costco offering by the device alone. The expertise of the person working with you is of utmost importance, especially if you've never used a hearing aid before. In fact, the price of a traditional hearing aid typically includes audiology services for years; which makes up at least half of the overall cost. Some users of Costco hearing aids report having great service performed by audiologists, while others had providers with less training or questionable expertise. We've heard of multiple accounts of long wait times for follow-up appointments, and sub-optimal care generally. It seems that in terms of the availability of expert audiologists and the quality of services, Costco is a mixed bag. All things considered though, the Costco Kirkland Signature 10 hearing aids are a great value. If you have a Costco nearby, they're worth your consideration.

The Knobs interview Ralf Gottschalk founder of Wonderful Audio Technology, aka WAT?! Ralf has a fantastic new version of a dynamic reverb out and several other great things in the mix, and a great backstory. Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview the fantastic Lisa S. Johnson, famed guitar photographer and author of two amazing guitar books — 108 Rock Star guitars, and the newly released Immortal Axes: Guitars That Rock. Lisa has photographed over 600 guitars and she shares some amazing stories behind some of the most epic guitars ever played - Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Glyn Evans founder of Mr. Glyn's Pickups in Auckland, New Zealand! What a great time we had learning about his approach to guitar gear and of course pickups. Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Tony Dudzik and Rob Chafe      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

In this weeks episode we discuss 2 of the most popular Killshots bags, the 357 and P90! We also discuss the Pros and Cons of a Clean Vs Dirty Playstyle and when each one is more important! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app

The Knobs interview Mikey D aka Mike Diluccio a gigging musician, music teacher, massive gear enthusiast, and one of the long-time supporters of our show.  Mikey D is a huge supporter of the guitar community and we are grateful to have him on the show. Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Tony Dudzik and Rob Chafe      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Adam Grimm founder of the famous Satellite Amps out of San Diego, CA. Adam has created a wide range of amps for loads of tone, that have graced stages all over the world. Each one is hand-wired and constructed at Satellite.  He shared some incredible choices for his Four On The Floor too! Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Tony Dudzik and Rob Chafe      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Blake Kaiser founder of Kaisertronics a fantastic pedal builder from San Antonio, TX. Blake has a great eye for detail in every aspect of the build and presentation and his pedals ooze quality. Thanks for listening and enjoy the podcast! Hosted by Todd Novak with Jared Brandon and Tony Dudzik      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs welcome back to the show Alec Breslow of MAE aka Mask Audio Electronics. Alec has been a very busy dude and has really diversified his talents including a pretty epic limited release with Pine Box Customs. Listen to what he's been up to and enjoy the show! Hosted by Todd Novak with Tony Dudzik      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Instagram wonderboy, YouTuber, and massive gearhead William John Bennett III. Our friend from Canada regularly delights us all with his wit and great gear demos on his social channels and was a great guest!  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Grand Poohbah supporter Steve Keyes! Steve is a great supporter of the boutique guitar gear community and a great dude. He shares a great backstory on how he got into guitars and gear.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Kyle Wolfe founder of Moon Guitars out of New Jersey. Kyle caught our attention because he is creating some unique guitars for sure and we dive deep into his design choices, craft, and influences. Enjoy the show! Hosted by Todd Novak and Tony Dudzik      Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Chris Jahnle founder of Vaderin Pedals out of Pennsylvania. Chris has several pedals in his product line but is grabbing a lot of attention with his new pedal the pop art influenced HPX - His own take on the harmonic percolator type guitar pedal. Enjoy the show! Hosted by Todd Novak with Tony Dudzik and John Esterly     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Dave Hunter, lifetime musician and author of the FANTASTIC new book called Fender 75 years. Dave has authored numerous guitar books and is an international guitar magazine content contributor so, let's just say he knows what he is talking about. Dave was a great guest who we will surely hear more from in the future.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs do another great 101 episode about Rickenbacker guitars! Buckle up this is a long one but well worth it! Long time listeners know how much Tony loves Rickenbackers and knows a ton about them but we also have Kenny Howes, who spent many years employed by Rickenbacker and is a HUGE Rick enthusiast and talented musician as well  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

In another live from Stockholm, HLTV Confirmed teams up with YEKINDAR to talk through the excitement of the PGL Major arena stage: VP's run overviewed, NIP, FURIA, Vitality failure broken down, NAVI, G2 chances analyzed. In other topics are weapon balance, community, banter, the role of LAN pressure, potential s1mple's break, and Vitality's rumored reshuffle with ex-Astralis players. ➡️ Follow us for updates: https://twitter.com/HLTVconfirmed

The Knobs interview Bill & Phil the founders of Thimble Wasp Effects, a relatively new pedal effects brand based right here in our hometown of Columbus, Ohio! Bill & Phil make a great team and are making great pedals.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Connor Kelly, founder of High Spirit Guitars in San Diego, CA. Connor has found some unique ways to create his own styling for his guitars including his own pickup models and proprietary hardware.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Patrick Baldwin, founder of Radio Mule a boutique pedal brand out of Tacoma, WA. Patrick is a great guy making great noise machines. We get to debut his fantastic NEW pedal too! Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview James Sturner founder of Sturner Guitars another great builder out of Philadelphia, PA. James has literally carved a niche in the guitar world with his unique designs. He has a great story to share with us! Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Brad Tolinski and Chris Gill, authors of the new book "Eruption: Conversations With Eddie Van Halen. This is a special one for us as EVH was a guitar hero to so many of us. Brad and Chris offer a completely new look at guitar legend Eddie Van Halen with this groundbreaking oral history, composed of more than fifty hours of interviews with Eddie himself as well as his family, friends, and colleagues. Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Markus Reeves founder of Reeves Electro, a celebrated pedal effects builder in the UK. Markus is known for handcrafting his unique and frankly stunning suspended electrical layouts inside his pedals, which happen to sound amazing as well.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs interview Keith Horne, founder of Marvin Guitars. Keith is a lifelong musician based in Los Angeles, and has created a strong reputation building every guitar by hand, made to order.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

The Knobs get to spend some time with one of our own Grand Poohbah supporters Cody Foster. Cody is a guitar gear nut and a massive supporter of the guitar community. He also plays in a Cincinnati-based band called Armadeus and hosts That Vinyl Show Podcast.  Enjoy the show! Hosted by Todd Novak with Jared Brandon and Tony Dudzik     Guitar, electric guitar, guitar pedal, pedal effects, pedal fx, guitar amplifier, humbucker, single coil, P90, guitar pickups, guitar setup, fuzz, overdrive, delay, reverb, distortion, guitar player, guitarist, guitar tips, guitar repair, vintage guitar, guitar amp speakers, guitar cabinet, combo amp, guitar amp Visit us at theguitarknobs.com Support our show on Patreon.com/theguitarknobs

Join this channel to get access to perks: https://www.youtube.com/channel/UCUMBIYslSt3wQgJwWrDP5dQ/join Listen To The Podcast Here - https://anchor.fm/dylantalkstone Sponsored in part by Audible. Get your FREE audiobook here: http://www.audibletrial.com/dylantalkstone Learn to Solder and get 2 FREE months of Skillshare! https://skl.sh/2TRnbxe 0:00 Intro 10:20 Have you ever made hidden pickups 15:24 Does The Jazzmaster have a resistor on the bass circuit 19:00 How would you wire a 3 way to a P90 22:08 Does a Trim Block affect the tone 31:00 Modded Guitars Should Be Worth More Upload your music to Apple, Amazon, Spotify, and more. Use this link for a 7% discount: https://distrokid.com/vip/dylantalkstone Find us on the internets at: http://www.dylantalkstone.com http://www.facebook.com/dylantalkstone http://www.instagram.com/dylantalkstone http://www.twitter.com/dylantalkstone

Do you know your XG from your P90? Well this week, inspired by AC-12, we're talking football abbreviations. We're also putting ourselves in Southgate's shoes and picking who we think will stick around in the England squad and make it all the way to Qatar. Plus we fill out the footballer census. Learn more about your ad choices. Visit megaphone.fm/adchoices

P90: मेरी प्यारी यूट्यूब से साक्षात्कार । 1st interview with 6 yearold YouTuber. Sir aap se video or image sharing kre or viral bhi kre apne sabhi platform pr

Tony Horton is the wildly popular creator of the best-selling fitness series: P90X®, P90X2®, P90X3®, Ten Minute Trainer®, One On One with Tony Horton®, and his latest program he calls “The on-switch to fitness” P90®. Tony is a world-class motivational speaker and the author of top-selling books “Bring It”, Crush It!” and his latest motivational book, “The Big Picture” 11 Laws that will change your life. He has appeared on countless television programs as a fitness and lifestyle expert to promote healthy living through exercise and proper nutrition. Tony's latest endeavor is a TH Care, a line of moisturizers and shampoos geared toward the fitness community. For the past 25 years, he has used his unique brand of humor to change the lives of over 8 mil- lion people through his incredible fusion of motivation, physical exercise, nutrition, and discipline. From worldclass athletes, pro sports teams, celebrities and the U.S. Military, to corporate executives, couch potatoes, and busy moms and dads alike, Tony has what it takes to reach and teach them all. Tony believes that real and lasting change can happen when we commit to health as a lifestyle. Exercise, whole foods, and the right mindset is the formula that leads to a vibrant, productive and full life for anyone who focuses on being the best they can be.

Tony Horton is the wildly popular creator of the best-selling fitness series: P90X®, P90X2®, P90X3®, Ten Minute Trainer®, One On One with Tony Horton®, and his latest program he calls “The on-switch to fitness” P90®. Tony is a world-class motivational speaker and the author of top-selling books “Bring It”, Crush It!” and his latest motivational book, “The Big Picture” 11 Laws that will change your life. He has appeared on countless television programs as a fitness and lifestyle expert to promote healthy living through exercise and proper nutrition. Tony's latest endeavor is a partnership with 7-Eleven to offer fresh and healthy sandwiches, wraps, salads, and cold pressed juices, providing nutritious options to people on the go. For the past 25 years, he has used his unique brand of humor to change the lives of over 8 mil- lion people through his incredible fusion of motivation, physical exercise, nutrition, and discipline. From worldclass athletes, pro sports teams, celebrities and the U.S. Military, to corporate executives, couch potatoes, and busy moms and dads alike, Tony has what it takes to reach and teach them all. Tony believes that real and lasting change can happen when we commit to health as a lifestyle. Exercise, whole foods, and the right mindset is the formula that leads to a vibrant, productive and full life for anyone who focuses on being the best they can be. In This Episode: How change in location can be the jump start. The value in consistency. How many attempts it takes to create a successful product The value in exercise variation. How P90X got hooked up with Beachbody Tony's Favorite Quote: “Do your best and forget the rest” — Tony Horton Robert's Favorite Books: The Magic Lamp: Goal Setting for People Who Hate Setting Goals The Seat of the Soul: 25th Anniversary Edition with a Study Guide Spark: The Revolutionary New Science of Exercise and the Brain Get Your Free Audio Book Links From Today's Show:www.tonyhortonlife.com 30 Day Beachbody OnDemand Trial Today's Sponsor: www.iboommedia.com