Podcasts about faangs

The surge in US tech stocks, especially Nvidia's 143 per cent increase, has investors questioning if it's too late to invest. Genevieve Cua discusses strategies for tech stock investment and market trends with Dr Wei Dai from Dimensional Fund Advisors. Synopsis: Learn to protect and grow your wealth in this monthly Business Times podcast series for affluent individuals, hosted by BT wealth editor Genevieve Cua. Highlights of the podcast: 02:28 Outsized investment returns are not unusual in history 05:57 Markets are very concentrated in tech, but there are ways to balance this 10:22 Making sense of the Fed's rate cut 14:39 How and why science matters in investing --- Now, we want to hear from you! Send us your questions, thoughts, story ideas, and feedback to btpodcasts@sph.com.sg. We'll look into it for future episodes. --- Written and hosted by: Genevieve Cua (gen@sph.com.sg) With Dr Wei Dai, head of research and vice-president, Dimensional Fund Advisors Edited by: Howie Lim & Claressa Monteiro Produced by: Genevieve Cua & Howie Lim Engineered by: Chai Pei Chieh A podcast by BT Podcasts, The Business Times, SPH Media — Follow WealthBT podcasts and rate us at: Channel: bt.sg/btwealthbt Amazon: bt.sg/wbtam Apple Podcasts: bt.sg/wbAP Spotify: bt.sg/wbSP YouTube Music: bt.sg/wbyt  Website: bt.sg/btcorresp Do note: This podcast is meant to provide general information only. SPH Media accepts no liability for loss arising from any reliance on the podcast or use of third party's products and services. Please consult professional advisors for independent advice. Discover more BT podcast series: BT Money Hacks Podcast at: bt.sg/btmoneyhacks BT Mark To Market Podcast at: bt.sg/btmark2mkt BT Podcasts at: bt.sg/pcOM PropertyBT at: bt.sg/btpropertybt BT Market Focus at: bt.sg/btmktfocus BT Branded Podcasts: bt.sg/btbrpod BT Lens On: bt.sg/btlensonSee omnystudio.com/listener for privacy information.

In this episode, Dave and Jamison answer these questions: Long time listener, first time question asker. I love the show, thank you for all the advices :) I've been working in one of the FAANGs for around 3 years now. I joined the company at a lower level and for the past two years I received promotions that got me to a level I'm feeling good with. Having said that, my impact on the group and organization is higher than other people in my rank. Since I'm new to this rank, the chances of getting another promotion (the third in three years) is nearly impossible. I love my manager and I've raised it to him in a few meetings before but the answer was that I still don't have the seniority in that level to get a promotion. This feels extremely frustrating as it feels like up until now I was aiming on getting to the rank I should've been recruited at and now when I feel like I can honestly make the leap, it's not possible. I thought about moving to a different group within the company but since it's really hard to find good managers and he already knows me and my contributions, it feels like opening a new page somewhere else in the company might even take me backwards on the journey to my next promotion. What do you think I should do? Thank you!! Hey guys, I am constantly fighting the irrational fear of being fired from my job or even the slightest hint of getting PIP'd. So far I have not gotten any indication that I'm underperforming and I've actually been told I'm doing well but in stressful seasons (when prod goes down or when I'm taking too long to finish a story), I start spiraling. This happens every other month. Therapy hasn't worked. Being open with my manager hasn't worked. So now I'm wondering if Jamison and Dave have the secret sauce. Part of it is knowing since day 1 that this company doesn't hesitate to cut underperformers. Hearing the rumblings about the current market, I'm nervous that it would take me months to even a year to get a new job, and it has me freaking out. What can I do to just calm down?

In this episode with Hunter Horsley, CEO of Bitwise, we discuss:   Bitcoin creating a global standard and addressing the decline in trust in leaders and corporations Success of spot Bitcoin ETFs How much are institutions allocations -- 1%? 3%? 28%?! When will FAANGs invest in Bitcoin? Will all 11 ETF issuers survive?  Fragmentation in internet commerce and bank settlements ---- Bio: Hunter Horsley is the CEO and Co-Founder of Bitwise Asset Management, one of the largest cryptocurrency asset managers. The former Facebook product manager earned a Bachelor's in Economics from The Wharton School at University of Pennsylvania. Follow Hunter on X at https://x.com/HHorsley ---- Coin Stories is powered by Bitdeer Technologies Group (NASDAQ: BTDR), a publicly-traded leader in Bitcoin mining that stands alone as the only vertically-integrated, technology-focused Bitcoin mining company. Learn more at www.bitdeer.com.  ---- Natalie's Promotional Links:  Bitcoin Nashville is July 25-27th! Join me for my 3rd Annual Women of Bitcoin Brunch! Get 10% off your conference passes using the code HODL: https://b.tc/conference.  Buy Bitcoin, secure it through multisig collaborative custody, start a Bitcoin IRA or take out a Bitcoin loan with UNCHAINED: https://shorturl.at/jmW29 promo code Natalie  Never wait or pay high fees for making Bitcoin payments. Use Speed Lightning Wallet to instantly send and receive Bitcoin: https://speedbtcwallet.onelink.me/cGph/coinstories  Safely self-custody your Bitcoin with Coinkite and the ColdCard Wallet. Get 5% off: https://shorturl.at/apsLU  Master your Bitcoin self-custody with 1-on-1 help and gain peace of mind with the help of The Bitcoin Way: https://www.thebitcoinway.com/partners/natalie-brunell  Protect yourself from SIM Swaps that can hack your accounts and steal your Bitcoin. Join America's most secure mobile service, trusted by CEOs, VIPs and top corporations: https://www.efani.com/natalie  Don't waste hundreds of dollars per month on fiat health insurance. Join me at CrowdHealth, a large community of Bitcoiners passionate about health who crowdfund each other's care: www.crowdhealth.com/natalie   Connect with Bitcoiners and Bitcoin merchants wherever you live and travel on the Orange Pill App: https://shorturl.at/gvxS3 ---- This podcast is for educational purposes and should not be construed as official investment advice. ---- VALUE FOR VALUE — SUPPORT NATALIE'S SHOWS Strike ID https://strike.me/coinstoriesnat/ Cash App $CoinStories   #money #Bitcoin #investing

Investing in Bizarro World Episodes: https://youtube.com/playlist?list=PLIAfIjKxr02sAztzlJNy1ug5bDvTVZkME&si=w2d_EF-B5jMo1dYD Subscribe to Investing In Bizarro World: @bizarroworld We're all smart again as many asset classes are bullish and had a good week last week. The S&P is back to bullish. Rates are bullish. Gold and Copper are bullish. Oil is bullish. Bitcoin is bullish. And I could go on. We do go on about it in the 269th episode of Investing in Bizarro World. We also get into why, which includes relatively decent economic growth and commodity prices that are pushing inflation higher. Or is it inflation that's pushing commodity prices higher? We talk about that and other market-driving factors. We also talk about the emerging concept of FAANG 2.0, and a new group of stocks set to rise like the FAANGs of old, but for different reasons. There's a quick note on silver buddying up to gold, and the technical levels to watch in the precious metals space.And then a deeper dive on changing uranium fundamentals and narratives. Plus: a small tech stock we've been buying. It's all in the 269th episode of Investing in Bizarro World.0:00 Intro1:29 Everyone Is Smart Again: Stocks, Rates, Dollar, Gold, Copper Oil All Bullish6:10 Copper, Missiles & Resource Rockets: FAANG 2.015:58 Silver Buddies Up with Gold18:30 Uranium Chooses a Side26:33 Market Watching: MineHubVisit our website Daily Profit Cycle for more content like this and more! https://dailyprofitcycle.com/

Do you own the Magnificent 7? Do you remember FAANG stocks? Do these arbitrary groupings matter? Only if you keep score, as one listener reminds us! Yes, it's the mailbag time of the month again, where we hear from you about what you've learned, what you're teaching, and what you're looking forward to. Host: David Gardner Producer: Rick Engdahl

Kia ora,Welcome to Monday's Economy Watch where we follow the economic events and trends that affect Aotearoa/New Zealand.I'm David Chaston and this is the international edition from Interest.co.nz.And today we lead with news China's debt problems are just growing and more investors are worried.But first, in the week ahead we will get some key data. In the US, they have a Fed rate review on Thursday and markets will be eyeing signals about when rates might move. Some think a March cut is coming. Then on Saturday, the January non-farm payrolls report on their labour market is out. And PMIs, consumer sentiment data, and factory order data will round out their big economic signals. Their earnings season is in its third week and there are some very large companies reporting, including most of the FAANGs (or now more accurately, MAMAAs). EU GDP will come this week too along with CPI updates from them, South Korea and Australia (on Wednesday). Locally it will be building consent data and the large end of month stats dump from the RBNZ that will interest us.Over the weekend we got data on Chinese industrial profits which rose +16.8% in December above the same month last year. And that was the fifth straight month they have risen. But the bar is low. The year ended with overall profits -2.3% lower over the whole twelve months, and in calendar 2022 they had fallen -4.0%.2024 is going to be a tough year for Chinese corporates. They are facing a record obligation to pay bond debt maturities, which will total ¥6.8 tln, (or NZ$1.55 tln). Their problem is that creditors are either increasingly unwilling to roll it over, or will demand significantly higher interest rates to do so. Both scenarios will hurt, and the pain will grow as the year progresses. Debt obligations have been growing much faster than GDP, making creditors skittish. And in the three years to 2026 the redemption obligation rises to ¥20 tln, so the problems won't fade with time.In the recent past, investors have continued buying Local Government financing bonds (LGFVs) which are part of the overall corporate debt, assuming that they are guaranteed by the government. And none have failed outright yet. But these LGFV bonds linked to "infrastructure" (read, their property development sector) are based on unprofitable enterprises, and maturities are jumping 40% in 2024, accentuating the pressures. Recently, institutions have been dealing with this pressure with very high interest rates (8+%) and much shorter maturities (less than 3 years). It doesn't take a rocket scientists to see what is about to happen. This will only work out if Beijing underwrites everyone, which does seem increasingly unlikely. Xi won't be happy in the trap and will probably want to 'teach' the financial markets a lesson.The scale of the problem is highlighted in an updated report on the country's macro leverage ratio. It rose +13.5 percentage points in a year to 288% in 2023 as a measure of non-financial debt to GDP.To put off the reckoning, last week China rolled out some very large and unexpected stimulus, much of it targeted. Their central bank now seems to have an outsized role in these efforts and the signals are more is to come, with the central bank providing cheap funds via its "Pledged Supplemental Lending" programs. These recent moves cost about ¥3 tln in total.But investors from well-known global institutions and local icon firms at a Hong Kong Government promotion event last week cast doubts on how effective the policies would be. The event was supposed to talk things up, but in fact it just allowed participants to confirm that others share their gloom. So far, key concerns such as China's property crisis and low confidence appear unaddressed.Singapore was expecting to report a bounce-back in industrial production in December after the November fall. But it didn't happen. They reported another, albeit smaller, retreat. Analysts there aren't anticipating any significant improvement in the first half of 2024.American inflation seems to be cooling, and in a way that the US Fed will like. While overall PCE inflation was unchanged at 2.6%, their core PCE rate came in lower than expected at 2.9%, down from 3.2% in November. Remember this was running at almost 5% a year ago.And all this happened while personal spending rose in the December quarter, and by more than anticipated. Higher activity and lower inflation is a goldilocks outcome. 'Real' personal consumption is +3.2% higher than a year ago - that's after inflation!And to add to the vibe, personal income has come in +4.2% higher that year-ago levels on the same 'real' basis, showing households are more than keeping up with inflation.Markets are back thinking this might give the Fed an opportunity to reduce policy rates by mid-2024; some think as early as March. One thing on their mind with falling inflation and a policy rate at 5.5% is that real interest rates are effectively rising now.December American pending home sales also rose rather strongly in December, up +8.3% from November to finally to best year ago levels by +1.3%. They haven't had a gain like this outside the pandemic period since early 2017. A surge in California helped although most regions showed gains. And recall, we noted last week a similar strong rise in new home sales nationwide.The UST 10yr yield starts today at 4.14% and down -2 bps from this time Saturday. The price of gold will start today up another +US$3/oz from Saturday at just on US$2019/oz.Oil prices are up another +US$1 at just over US$78/bbl in the US while the international Brent price is now just over US$83/bbl.The Kiwi dollar starts today at just under 60.9 USc and marginally lower from this time Saturday. Against the Aussie we are unchanged at 92.7 AUc. Against the euro we are also unchanged at 56.1 euro cents. That all means our TWI-5 starts today at 69.9 and unchanged since Saturday and little-changed in a week.The bitcoin price starts the week firmer again. It is now at US$42,307 which is up +0.9% from this time Saturday. Volatility over the past 24 hours has been modest at just on +/- 1.3%.You can find links to the articles mentioned today in our show notes.You can get more news affecting the economy in New Zealand from interest.co.nz.Kia ora. I'm David Chaston. And we will do this again tomorrow.

Consultorio y Formación con Admirals España. Franco Macchiavelli nos habla del sentimiento del mercado en una sesión sin la principal referencia de Wall Street cerrado por festivo. En opinión de Franco Macchiavelli, el foco esta semana debe estar en un mix de varias cosas: en términos técnicos, el SP500 está en plena resistencia de máximos históricos; los últimos datos macro revelan repuntes inflacionistas y en tercer lugar, los resultados empresariales que han empezado a publicarse en EEUU. Comenzamos respondiendo las consultas de los oyentes, que preguntan por Santander. Nos dice el experto de Admirals España que vigilaría el nivel de los 3,6 euros por acción. De Acerinox, que ha cerrado en 10,40 euros, Franco Macchiavelli prestaría atención al techo en 11,4 euros y el suelo, en la zona de 9 euros. También preguntan por tecnológicas americanas y si se podría entrar en alguna de las FAANGS y a qué precios. En este punto, le gusta especialmente Apple en los 170 dólares y Meta, aunque aquí esperaría un poquito a cualquier retroceso que se acerque a los 330 dólares para darnos una oportunidad. Seguimos en EEUU, los resultados de JPMorgan que publicó el pasado viernes han sido muy buenos y la acción está ya muy cerquita de máximos históricos, la resistencia la tendría en los 170 dólares y esperaría un retroceso hasta los 137-140 dólares. Volviendo al mercado español, nos pregunta un oyente por Indra compradas 13,93 euros. Para Franco Macchivelli, el oyente compró justamente en el momento en que el mercado marcó un nuevo impulso. Es verdad que el valor viene comportándose muy bien, técnicamente desde septiembre de 2022 registra muy buena pauta alcista pero iría con cuidado porque estamos llegando a resistencias de los 14,5 euros. Por último, sobre sector salud, nos interesamos por dos farmas: Rovi y Sanofi. De la farmacéutica española, dice que tuvo muy buen desempeño en la zona de 39, 40 euros aunque ahora está sobrecomprada y el experto de Admirals España vigilaría el nivel de los 45 euros. Y la francesa Sanofi, por último, está muy lateral.. hasta que no salga de la zona de 80-100 euros, no entraría.

Debates about inequality often focus on inequalities between people. But what about inequalities between firms?Recent decades have seen the emergence of giant, multinational firms - the FAANGs of this world. But over 40% of registered businesses in the UK have less than 10 employees.What do we mean when we talk about inequality between firms? Are inequalities between firms limiting UK business dynamism? And do governments need to step in and enforce competition rules?Joining us this episode are John Van Reenan, Ronald Coase Chair in Economics and School Professor at the LSE, and Amelia Fletcher, Professor of Competition Policy at Norwich Business School.Find out more: https://ifs.org.uk/inequality/Become a member: https://ifs.org.uk/individual-membership Hosted on Acast. See acast.com/privacy for more information.

On today's episode of FYI we will be featuring last week's episode of In The Know, a monthly video series in which ARK CEO and CIO Cathie Wood discusses Fiscal Policy, Monetary Policy, Economic and Market Indicators and Innovation. On this specific episode, Cathie Wood, weighs in on artificial intelligence (AI), Bitcoin, Fed Policy, electric vehicles, the discrepancy between GDP and GDI, bankruptcies, and the German and Chinese economies. Watch the video version here. Key Points From This Episode: Lagging and leading market indicators Rising bankruptcies The Fed's policy, as indicated by the latest Fed meeting minutes The discrepancy between Gross Domestic Product (GDP) and Gross Domestic Income (GDI) The potential for a hard economic landing Bitcoin, and a potential spot Bitcoin ETF An apparent increase in demand for Electric Vehicles The current state of the German and Chinese economies The Artificial Intelligence Revolution Glossary of Terms “Fed” refers to the U.S. Federal Reserve, the central banking system of the United States. Fed Funds Rate is the interest rate at which depository institutions (banks and credit unions) lend reserve balances to other depository institutions overnight on an uncollateralized basis. M2 is the U.S. Federal Reserve's estimate of the total money supply including all of the cash people have on hand plus all of the money deposited in checking accounts, savings accounts, and other short-term saving vehicles such as certificates of deposit (CDs). Yield Curve is a graphical representation of the interest rates on debt for a range of maturities. It shows the yield an investor is expecting to earn if they lend their money for a given period of time. An inverted curve appears when long-term yields fall below short-term yields. An inverted yield curve occurs due to the perception of long-term investors that interest rates will decline in the future. A Basis Point is equal to 1/100th of a percentage point (100 basis points = 1%). Gross Domestic Product (GDP) is the total monetary or market value of all the finished goods and services produced within a country's borders in a specific time period. Nominal GDP is a measure of economic output that uses current prices and does not adjust for inflation. “CPI” refers to the Consumer Price Index, which is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Core CPI excludes food and energy. “Magnificent 7” is a term adopted by the financial industry to describe the top seven technology companies currently investing heavily in artificial intelligence (AI). The seven companies are Meta Platforms, Alphabet, Apple, Amazon, Microsoft, Nvidia and Tesla. The previously used “FAANGs” acronym, coined in 2017, described the top technology companies at the time and included Meta Platforms (f/k/a Facebook), Apple, Amazon, Netflix and Google (now trading under its parent company, Alphabet). “Mega-caps” refers to companies with market capitalizations in excess of $200 billion. Market capitalization refers to the total dollar market value of a company's outstanding shares of stock. The S&P 500 is a stock market index tracking the stock performance of 500 of the largest companies listed on stock exchanges in the United States. The Nasdaq-100 is a stock market index made up of 101 equity securities issued by 100 of the largest non-financial companies listed on the Nasdaq stock exchange. “QQQs” refers to the Invesco QQQ Trust ETF which is a passive ETF that tracks the Nasdaq 100 Index and therefore is sometimes used as a proxy for the index in conversation.

Against a backdrop of somewhat quieter markets, we ask what are short-term Treasuries telling us about debt ceiling negotiations? What's behind the strong performance of US technology stocks? And why does China need to revitalise its property sector? Ben Bennett explains all. This episode is hosted by Frances Watson, Content Manager. All data sourced from Eikon as at 22 May. For professional investors only. Capital at risk.

In this week's podcast FXCM senior market specialists, Nik and Russ, talk about: · CPI came as expected. Headline was at 6.5% (6.5%). Core was 5.7% also around expectations, lowest reading in over a year. o Following release, CME Fed watch tool had over 90% chance of 25bps. o Markets are loose, worth watching. o Brainard, Waller and other speaking this week. § Will they talk hawkishly or not? o Harker from Philly maintained 25bps. · World Bank 2023 GDP growth slashed. · Banks earnings: markets reacted positively but some questions. o Dealmaking is down. o Credit costs are up · Bank of Japan – will they abandon yield curve control? o 50bps has already been breached. · CPI: CAD, UK, Eurozone. · Wed PPI à in relation to CPI · Retail sales: US, CAD, UK · NFLX on Thur (first of FAANGS)

What's going to happen to the sports media and streaming market in 2023? We asked Bundle regulars Yannick Ramcke and Murray Barnett for their hopes, fears and predictions for the year ahead.Price hikes, subscription wars, economic woes and OTT white elephants; it's all here. Plus what the year holds for Disney, Sky, DAZN, the FAANGs and the a host of Drive to Survive wannabes. Unofficial Partner is the leading podcast for the business of sport. A mix of entertaining and thought provoking conversations with a who's who of the global industry. To join our community of listeners, sign up to the weekly UP Newsletter and follow us on Twitter @UnffclPrtnr

Subscribe to Changelog++: https://changelog.com/podcast/519/discussFeaturing Shawn Wang – Twitter, GitHub, Website Adam Stacoviak – Mastodon, Twitter, GitHub, LinkedIn, Website Jerod Santo – Mastodon, Twitter, GitHub, LinkedIn Notes and Links AI Notes Why “Prompt Engineering” and “Generative AI” are overhyped Multiverse, not Metaverse The Particle/Wave Duality Theory of Knowledge OpenRAIL: Towards open and responsible AI licensing frameworks Open-ish from Luis Villa ChatGPT for Google The Myth of The Infrastructure Phase ChatGPT examples in the wild Debugging code TypeScript answer is wrong Fix code and explain fix dynamic programming Translating/refactoring Wasplang DSL AWS IAM policies Code that combines multiple cloud services Solving a code problem Explain computer networks homework Rewriting code from elixir to PHP Turning ChatGPT into an interpreter for a custom language, and then generating code and executing it, and solving Advent of Code correctly Including getting #1 place “I haven't done a single google search or consulted any external documentation to do it and I was able to progress faster than I have ever did before when learning a new thing.” Build holy grail website and followup with framework, copy, repsonsiveness For ++ subscribers Getting Senpai To Notice You Moving to Obsidian as a Public Second Brain Transcript**Jerod Santo:** Alright, well we have Sean Wang here again. Swyx, welcome back to the show.**Shawn Wang:** Thanks for having me back on. I have lost count of how many times, but I need to track my annual appearance on the Changelog.**Adam Stacoviak:** Is that twice this year on this show, and then once on JS Party at least, right?**Shawn Wang:** Something like that, yeah. I don't know, it's a dream come true, because, I changed careers into tech listening to the Changelog, so every time I'm asked on, I'm always super-grateful. So yeah, here to chat about all the hottest, latest things, right?**Adam Stacoviak:** Yeah.**Jerod Santo:** That's right, there's so much going on right now. It seems like things just exploded this fall. So we had Stable Diffusion back in late August; it really blew up at the end of August. And then in September is when we had Simon Willison on the show to talk about Stable Diffusion breaking the internet. You've been tracking this stuff really closely. You even have a Substack, and you've got Obsidian notes out there in the wild, and then of course, you're learning in public, so whenever Swyx is learning something, we're all kind of learning along with you... Which is why we brought you back on. I actually included your Stable Diffusion 2.0 summary stuff in our Changelog News episode a couple of weeks back, and a really interesting part of that post that you have, that I didn't talk about much, but I touched on and I want you to expand upon here is this idea of prompt engineering, not as a cool thing, but really as a product smell. And when I first saw it, I was like, "No, man, it's cool." And then I read your explainer and I'm like, "No, he's right. This is kind of a smell."**Adam Stacoviak:** "Dang it, he's right again."**Jerod Santo:** Yeah. We just learned about prompt engineering back in September, with Simon, and talking about casting spells and all this, and now it's like, well, you think it's overhyped. I'll stop prompting you, and I'll just let you engineer an answer.**Jerod Santo:** Well, so I don't know if you know, but the Substack itself got its start because I listened to the Simon episode, and I was like, "No, no, no. Spellcasting is not the way to view this thing. It's not something we glorify." And that's why I wrote "Multiverse, not Metaverse", because the argument was that prompting is -- you can view prompting as a window into a different universe, with a different seed, and every seed is a different universe. And funny enough, there's a finite number of seeds, because basically, Stable Diffusion has a 512x512 space that determines the total number of seeds.So yeah, prompt engineering [unintelligible 00:04:23.23] is not my opinion. I'm just reporting on what the AI thought leaders are already saying, and I just happen to agree with it, which is that it's very, very brittle. The most interesting finding in the academic arena about prompt engineering is that default GPT-3, they ran it against some benchmarks and it came up with like a score of 17 out of 100. So that's a pretty low benchmark of like just some logical, deductive reasoning type intelligence tests. But then you add the prompt "Let's think step by step" to it, and that increases the score from 17 to 83... Which is extremely -- like, that sounds great. Like I said, it's a magic spell that I can just kind of throw onto any problems and make it think better... But if you think about it a little bit more, like, would you actually use this in a real work environment, if you said the wrong thing and it suddenly deteriorates in quality - that's not good, and that's not something that you want to have in any stable, robust product; you want robustness, you want natural language understanding, to understand what you want, not to react to random artifacts and keywords that you give.Since then, we actually now know why "Let's think step by step" is a magic keyword, by the way, because -- and this is part of transformer architecture, which is that the neural network has a very limited working memory, and if you ask a question that requires too many steps to calculate the end result, it doesn't have the working memory to store the result, therefore it makes one up. But if you give it the working memory, which is to ask for a longer answer, the longer answer stores the intermediate steps, therefore giving you the correct result.**Jerod Santo:** [06:00] Talk about implementation detail, right?**Shawn Wang:** It's yeah, it's leaking implementation detail, it's not great, and that's why a lot of the thought leaders - I think I quoted Andrej Karpathy, who was head of AI at Tesla, and now he's a YouTuber... [laughter] And Sam Altman, who is the CEO of -- yeah, he quit Tesla to essentially pursue an independent creator lifestyle, and now he's a YouTuber.**Jerod Santo:** I did not know that.**Adam Stacoviak:** All roads lead to creator land, you know what I'm saying? You'll be an expert in something for a while, and eventually you'll just eject and be like "I want to own my own thing, and create content, and educate people around X."**Shawn Wang:** So at my day job I'm a head of department now, and I work with creators, and some of them have very valuable side hustles... And I just had this discussion yesterday, of like "Why do you still have a job if you're an independent creator? Like, isn't total independence great." And I had to remind them, "No. Like, career progression is good. You're exposed to new things etc." but that's just me trying to talk him out of quitting. [laughter] No, I have a serious answer, but we're not here to talk about that.**Jerod Santo:** Right.**Shawn Wang:** So I'll read out this quote... So Sam Altman, CEO of OpenAI, says "I don't think we'll still be doing prompt engineering in five years. It's not about figuring out how to hack the prompt by adding one magic word to the end that changes everything else. What will matter is the quality of ideas and the understanding that you want." I think that is the prevailing view, and I think as people change models, they are understanding the importance of this.So when Stable Diffusion 1 came out, everyone was like, "Alright, we know how to do this. I'm going to build an entire business on this" etc. And then Stable Diffusion 2 came out and everything broke. All the [unintelligible 00:07:40.21] stopped working, because they just expected a different model, and you have to increase your negative prompting, and people are like "What is negative prompting?" etc. These are all new techniques that arise out of the model, and this is going to happen again and again and again, because you're relying on a very, very brittle foundation.Ultimately, what we want to get people to is computers should understand what we want. And if we haven't specified it well enough, they should be able to ask us what we want, and we should be able to tell them in some capacity, and eventually, they should produce something that we like. That is the ultimate alignment problem.We talk about AI a lot, and you hear about this alignment problem, which is basically some amount of getting it to do what we want it to do, which is a harder problem than it sounds until you work with a programmer, and try to give them product specs and see how many different ways they can get it wrong. But yeah, this is an interesting form of the alignment problem, and it interestingly has a very strong tie with Neuralink as well, because the problem, ultimately, is the amount of bandwidth that we can transfer from our brain to an artificial brain. And right now it's prompts. But why does it have to be prompts? It could be images. That's why you have image-to-image in Stable Diffusion. And it could also be brain neural connections. So there's a lot in there; I'll give you time to pick on whatever you respond to...**Jerod Santo:** Well, I went from -- so I was super-excited about prompting after talking with Simon a few months back, and I was super-excited about Stable Diffusion. And I went from like giddy schoolboy who's just like "Gonna learn all the spells" very quickly to like aggravated end user who's like "Nah, I don't want to go to this other website and copy and paste this paragraph of esoterica in order to get a result that I like." And so I wonder what's so exciting about the whole prompt engineering thing to us nerds, and I think maybe there's like a remnant of "Well, I still get to have esoteric knowledge" or "I still get to be special somehow if I can learn this skill..."[09:46] But in reality, what we're learning, I think, by all the people using ChatGPT - the ease of use of it, as opposed to the difficulty of getting an image out of Stable Diffusion 1.0 at least, is quite a bit different. And it goes from aggravating and insider baseball kind of terms, keywords, spells, to plain English, explain what you want, and maybe modify that with a follow-up, which we'll get into ChatGPT, but we don't necessarily have to go into the depths of that right now... But I changed very quickly, even though I still thought prompt engineering was pretty rad... And then when you explain to me how Stable Diffusion 2 completely broke all the prompts, I'm like, "Oh yeah, this is a smell. This doesn't work. You can't just completely change the way it works on people..." That doesn't scale.**Shawn Wang:** Yeah. And then think about all the businesses that have been built already. There haven't been any huge businesses built on Stable Diffusion, but GPT-3 has internal models as well. So Jasper recently raised like a 1.5 billion valuation, and then ChatGPT came out, basically validating Jasper... So all the people who bought stock are probably not feeling so great right now. [laughs]That's it. So I don't want to overstate my position. There are real moats to be built around AI, and I think that the best entrepreneurs are finding that regardless of all these flaws. The fact that there are flaws right now is the opportunity, because so many people are scared off by it. They're like, "AI has no moats. You're just a thin wrapper around OpenAI." But the people who are real entrepreneurs figure it out. So I think it's just a really fascinating case study in technology and entrepreneurship, because here's a new piece of technology nobody knows how to use and productize, and the people who figure out the playbook are the ones who win.**Adam Stacoviak:** Yeah. Are we back to this -- I mean, it was like this years ago, when big data became a thing... But are we back to this whole world where -- or maybe we never left, where "Data is the new oil", is the quote... Because to train these models, you have to have data. So you could be an entrepreneur, you could be a technologist, you could be a developer, you could be in ML, you could be whatever it might take to build these things, but at some point you have to have a dataset, right? Like, how do you get access to these datasets? It's the oil; you've got to have money to get these things, you've got to have money to run the hardware to enable... Jerod, you were saying before the call, there was speculation of how much it costs to run ChatGPT daily, and it's just expensive. But the data is the new oil thing - how does that play into training these models and being able to build the moat?**Shawn Wang:** Yeah. So one distinction we must make there is there is a difference between running the models, which is just inferences, which is probably a few orders of magnitude cheaper than training the models, which are essentially a one-time task. Not that many people continuously train, which is nice to have, but I don't think people actually care about that in reality.So the training of the models ranges between -- and let's just put some bounds for people. I love dropping numbers in podcasts, by the way, because it helps people contextualize. You made an oblique reference to how much ChatGPT costs, but let's give real numbers. I think the guy who did an estimate said it was running at $3 million a month. I don't know if you heard any different, but that's...**Jerod Santo:** I heard a different estimate, that would have been more expensive, but I think yours is probably more reliable than mine... So let's just go with that.**Shawn Wang:** I went through his stuff, and I was like, "Yeah, okay, this is on the high end." I came in between like one to three as well. It's fine. And then for training the thing - so it's widely known or widely reported that Stable Diffusion cost 600k for a single run. People think the full thing, including R&D and stuff, was on the order of 10 million. And GPT-3 also costs something on the order of tens of millions. So I think that is the cost, but then also that is training; that is mostly like GPU compute. We're not talking about data collection, which is a whole other thing, right?[13:46] And I think, basically, there's a towering stack of open source contributions to this data collective pool that we have made over time. I think the official numbers are like 100,000 gigabytes of data that was trained for Stable Diffusion... And it's basically pooled from like Flickr, from Wikipedia, from like all the publicly-available commons of photos. And that is obviously extremely valuable, because -- and another result that came out recently that has revolutionized AI thinking is the concept of Chinchilla Laws. Have you guys covered that on the show, or do I need to explain that?**Adam Stacoviak:** Chinchilla Laws misses the mark for me. Please tell. I like the idea though; it sounds cool, so please...**Shawn Wang:** Yeah, they just had a bunch of models, and the one that won happened to be named Chinchilla, so they kind of went with it. It's got a cute name. But the main idea is that we have discovered scaling laws for machine learning, which is amazing.So in the sort of classical understanding of machine learning, you would have a point at which there's no further point to train. You're sort of optimizing for a curve, and you get sort of like diminishing returns up to a certain point, and then that's about it. You would typically conclude that you have converged on a global optimum, and you kind of just stop there. And mostly, in the last 5 to 10 years, the very depressing discovery is that this is a mirage. This is not a global optimum, this is a local optimum... And this is called the Double Dissent Problem. If you google it, on Wikipedia you'll find it... Which is you just throw more data at it, it levels off for a bit, and then it continues improving. And that's amazing for machine learning, because that basically precipitated the launch of all these large models. Because essentially, what it concludes is that there's essentially no limit to how good these models are, as long as you can throw enough data at it... Which means that, like you said, data is the new oil again, but not for the old reason, which is like "We're gonna analyze it." No, we're just gonna throw it into all these neural nets, and let them figure it out.**Adam Stacoviak:** Yeah. Well, I think there's a competitive advantage though if you have all the data. So if you're the Facebooks, or if you're the Google, or X, Y, or Z... Instagram, even. Like, Instagram ads are so freakin relevant that --**Jerod Santo:** Apple...**Adam Stacoviak:** Yeah, Apple for sure.**Jerod Santo:** TikTok...**Adam Stacoviak:** Yeah. Gosh... Yeah, TikTok. Yeah, the point is, these have a competitive advantage, because they essentially have been collecting this data, would-be to analyze, potentially to advertise to us more, but what about in other ways that these modes can be built? I just think like, when you mentioned the entrepreneurial mind, being able to take this idea, this opportunity as this new AI landscape, to say, "Let me build a moat around this, and not just build a thin layer on top of GPT, but build my own thing on all together", I've gotta imagine there's a data problem at some point, right? Obviously, there's a data problem at some point.**Shawn Wang:** So obviously, the big tech companies have a huge headstart. But how do you get started collecting this data as a founder? I think the story of Midjourney is actually super-interesting. So between Midjourney, Stability AI and OpenAI, as of August, who do you think was making the most money? I'll give you the answer, it was Midjourney.**Jerod Santo:** Oh, I was gonna guess that. You can't just give us the answer...**Shawn Wang:** Oh... [laughs]**Jerod Santo:** I had it.**Shawn Wang:** But it's not obvious, right? Like, the closed source one, that is not the big name, that doesn't have all the industry partnerships, doesn't have the celebrity CEO, that's the one that made the most money.**Jerod Santo:** Yeah. But they launched with a business model immediately, didn't they? They had a subscription out of the box.**Shawn Wang:** Yeah, they did. But also, something that they've been doing from the get-go is that you can only access Midjourney through Discord. Why is that?**Jerod Santo:** Right. Because it's social, or... I don't know. What do you think? That's my guess, because they're right in front of everybody else.**Shawn Wang:** Data.**Adam Stacoviak:** Data.**Jerod Santo:** Oh...**Adam Stacoviak:** Please tell us more, Shawn.**Shawn Wang:** Because the way that you experience Midjourney is you put in a prompt, it gives you four images, and you pick the ones that you like for enhancing. So the process of using Midjourney generates proprietary data for Midjourney to improve Midjourney. So from v3 to v4 of Midjourney they improved so much that they have carved out a permanent space for their kind of visual AI-driven art, that is so much better than everyone else because they have data that no one else has.**Jerod Santo:** [17:55] That's really cool.**Adam Stacoviak:** And that's relevance, or is it like quality takes? What is the data they actually get?**Shawn Wang:** Preference, right?**Jerod Santo:** What's good.**Shawn Wang:** Yeah. Literally, you type in a prompt, unstructuredly it tells you -- they give you four low-res images, and you have to pick one of the four to upscale it. By picking that four, they now have the data that says "Okay, out of these four, here's what a human picks." And it's and it's proprietary to them, and they paid nothing for it, because it's on Discord. It's amazing.**Jerod Santo:** That is awesome.**Shawn Wang:** They didn't build a UI, they just used Discord. I don't know if Discord knows this, or cares... But it's pretty freakin' phenomenal...**Jerod Santo:** That's pretty smart.**Shawn Wang:** ...because now they have this--**Adam Stacoviak:** It's the ultimate in scrappy, right? It's like, by any means necessary. That's the ultimate binding that's necessary, right? You'll make a beat however you can to put up the track and become the star.**Jerod Santo:** Right.**Adam Stacoviak:** That's amazing.**Jerod Santo:** That's really cool.**Shawn Wang:** So just to close this out, the thing I was saying about Chinchilla was "More data is good, we've found the double descent problem. Now let's go get all the data that's possible." I should make a mention about the open source data attempts... So people understand the importance of data, and basically Luther.AI is kind of the only organization out there that is collecting data that anyone can use to train anything. So they have two large collections of data called The Stack and The Pile, I think is what it's called. Basically, the largest collection of open source permissively-licensed text for you to train whatever language models you want, and then a similar thing for code. And then they are training their open source equivalents of GPT-3 and Copilot and what have you. But I think those are very, very important steps to have. Basically, researchers have maxed out the available data, and part of why Open AI Whisper is so important for OpenAI is that it's unlocking sources of text that are not presently available in the available training data. We've basically exhausted, we're data-constrained in terms of our ability to improve our models. So the largest source of untranscribed text is essentially on YouTube, and there's a prevailing theory that the primary purpose of Whisper is to transcribe all video, to get text, to train the models... [laughs] Because we are so limited on data.**Adam Stacoviak:** Yeah. We've helped them already with our podcasts. Not that it mattered, but we've been transcribing our podcasts for a while, so we just gave them a leg up.**Shawn Wang:** You did.**Adam Stacoviak:** And that's open source on GitHub, too. They probably -- I mean, ChatGPT knows about Changelog. They know that -- Jerod, I don't know if I told you this yet, but I prompted that; I said "Complete the sentence "Who's the hosts of the Changelog podcast?" "Well, that's the dynamic duo, Jerod Santo and Adam Stacoviak." It knows who we are. I mean, maybe it's our transcripts, I don't know, but it knows...**Jerod Santo:** Please tell me it called us "the dynamic duo"... [laughs]**Adam Stacoviak:** I promise you!**Jerod Santo:** It said that?**Adam Stacoviak:** I promise you it said that. "The dynamic duo..."**Jerod Santo:** Oh, [unintelligible 00:20:34.05]**Adam Stacoviak:** It actually reversed the order. It said Adams Stacoviak first and then Jerod Santo... Because usually, my name is, I guess, first, because - I have no clue why it's ever been that way, but... It said "The dynamic duo, Adam Stacoviak and Jerod Santo..."**Jerod Santo:** That's hilarious.**Adam Stacoviak:** ...hosts of the Changelog Podcast.**Jerod Santo:** It already understands flattery.**Adam Stacoviak:** Yeah, it does. Well, actually, the first prompt didn't include us, and I said "Make it better, and include the hosts." And that's all I said, was "Make it better and include the hosts." So in terms of re-prompting, or refining the response that you get from the prompts - that to me is like the ultimate human way to conjure the next available thing, which is try again, or do it better by giving me the hosts, too. And the next one was flattery, and actually our names in the thing. So... It's just crazy. Anyways...**Shawn Wang:** Yeah, so that is the big unlock that ChatGPT enabled.**Jerod Santo:** Totally.**Shawn Wang:** Which is why usually I take a few weeks for my takes to marinate, for me to do research, and then for me to write something... But I had to write something immediately after ChatGPT to tell people how important this thing is. It is the first real chat AI, which means that you get to give human feedback. And this theme of reinforcement learning through human feedback is - the low-res version of it was Midjourney. Actually, the lowest-res version of it was TikTok, because every swipe is human feedback. And being able to incorporate that into your -- and same for Google; every link click is a is human feedback. But the ability to incorporate that and to improve the recommendations and the generations is essentially your competitive advantage, and being able to build that as part of your UI... Which is why, by the way, I have been making the case that frontend engineers should take this extremely seriously, because guess who's very good at making a UI?**Adam Stacoviak:** Yeah, for sure.**Shawn Wang:** But yeah, ChatGPT turns it from a one-off zero-shot experience where you prompt the thing, and then you get the result, and it's good or bad, that's about the end of the story - now it's an interactive conversation between you and the bot, and you can shape it to whatever you want... Which is a whole different experience.**Break:** [22:31]**Adam Stacoviak:** "Complete the sentence" has been a hack for me to use, particularly with ChatGPT. "Complete the sentence" is a great way to easily say "Just give me somebody long, given these certain constraints."**Jerod Santo:** Well, that's effectively what these models are, right? They're auto-complete on steroids. Like, they are basically auto-completing with a corpus of knowledge that's massive, and guessing what words semantically should come next, kind of a thing... In layman's terms; it's more complicated than that, of course, but they are basically auto-completers.**Adam Stacoviak:** Yeah. On that note though, we have a show coming out... So we're recording this on a Friday, the same day we release the same podcast, but it's the week before. So we had Christina Warren on, and so I was like "You know what? I'm gonna use ChatGPT to give me a leg up. Let me make my intro maybe a little easier, and just spice it up a little bit." So I said "Complete the sentence "This week on the Changelog we're talking to Christina Warren about..." and then I ended the quote, and I said "and mention her time at Mashable, film and pop culture, and now being a developer advocate at GitHub." And I've gotta say, most of, 50% of the intro for the episode with Christina is thanks to ChatGPT. I don't know if I break the terms of service by doing that or not, but like -- do I? I don't know. If I do, sue me. I'm sorry. But... Don't sue me. Don't sue us. We'll take it down. We'll axe it out.**Jerod Santo:** We'll rewrite it.**Adam Stacoviak:** Yeah, we'll rewrite it. But, I mean, it's basically what I would have said. So...**Shawn Wang:** There's a nice poetry -- there's a YouTuber who's been on this forever, Two Minute Papers, and what he often says is, "What a time to be alive." And this is very much what a time to be alive. But not just because we're seeing this evolve live, but because we get to be part of the training data. And there was a very interesting conversation between Lex Fridman and Andrej Andrej Karpathy; he was inviting him on to the show... He said, "Our conversation will be immortalized in the training data. This is a form of immortality, because we get to be the first humans essentially baked in." [laughter]**Jerod Santo:** Essentially baked in... Hello, world.**Shawn Wang:** Like, 100-200 years from now, if someone has the Changelog podcast, they will keep having Jerod and Adam pop up, because they're in the goddamn training data. [laughs]**Jerod Santo:** They're like "Come on, these guys have been dead for a long time."**Adam Stacoviak:** [26:05] Let them go. Give them their RIP. [laughter]**Shawn Wang:** Which is poetic and nice. Yeah.**Adam Stacoviak:** Yeah, it is a good time to be alive... I think it is interesting, too... I just wonder -- I mean, this might be jumping the shark a little bit, but I often wonder, at what point does humanity stop creating? And at some point, 100 years from now, or maybe more, I don't know, we're gonna be -- maybe sooner, given how fast this is advancing, that we'll create only through what was already created. "At what point is the snake eating the snake?" kind of thing. Like, is there an end to human creativity at some point, because we are just so reliant, at some point, shape, or form, on [unintelligible 00:26:45.20] because of training data, and this just kind of like morphing to something much, much bigger in the future?**Shawn Wang:** So I have an optimistic attitude to that... This question basically is asking, "Can we exhaust infinity?" And so my obvious answer is no. There is a more concrete stat I can give you, which is I think - this is floating around out there. Don't quote me on the exact number, but apparently, 10% of all Google searches every single year have never been asked before. And Google's been around for like 20 years.**Adam Stacoviak:** That's a big percentage.**Shawn Wang:** It's still true. So it's on that order; it might be like 7%, it might be 13%.**Adam Stacoviak:** Well, is it trending down though? Is it trending down? Is it 10% per year, but is it like trending down to like 8%?**Jerod Santo:** Is it because we put the year in our searches? [laughter]**Adam Stacoviak:** Yeah, it's true, Jerod. Good one.**Shawn Wang:** Yeah. But anyway, so that's what the SEO people talk about when they talk about long tail... The amount of infinity is always bigger than our capability of creating to fill it.**Jerod Santo:** I mean, I feel like if you look at us in an abstract way, humans, we are basically taking in inputs and then generating outputs. But that's creativity, right? So I think what we're just doing is adding more to the inputs. Now we have computers that also take in inputs and generate outputs, but like, everything's already a remix, isn't it? Our life experience and everything that goes into us, and then something else produces a brand new thing, which isn't really new, but it's a remix of something else that we experienced... So I feel like we're just going to keep doing that, and we'll have computer aid at doing that, and the computer eventually maybe will just do the actual outputting part, but we somehow instruct it. I'm with Swyx on this one; I don't think there's going to be an end to human creativity, as the AI gets more and more output... What's the word? When you're just -- not notorious. What's it called when you just can't stop outputting stuff?**Adam Stacoviak:** I don't know.**Jerod Santo:** Prolific!**Adam Stacoviak:** Prolific.**Jerod Santo:** As the AI gets more and more output-prolific, and overwhelms us with output, I think we're still going to be doing our thing.**Adam Stacoviak:** Yeah. It's the ultimate reduction in latency to new input, right? Think of 100 years ago - creative folks were few and far between. They had miles between them, depending on your system; maybe it's kilometers. No offense. But there's distance of some sort of magnitude, and the lack of connection and shared ideas. So that's the latency, right? And now, the latency to the next input is just so small in comparison, and will get reduced to basically nothing. So we'll just constantly be inputting and outputting creativity, we'll just become like a creative [unintelligible 00:29:31.17] system with zero latency, nonstop creativity... Go, go, go...**Shawn Wang:** Well, I think this is where you start -- I don't know about you, but I feel a little bit uncomfortable with that, right? Entropy is always increasing in the universe; we're contributing to increasing noise and not signal. And that is a primary flaw of all these language models, is just they are very confidently incorrect. They have no sense of physics, no sense of logic; they will confidently assert things that are not true, and they're trained on sounding plausible, rather than being true.**Jerod Santo:** Right. They're kind of like me when I was in college, you know?**Shawn Wang:** Exactly. [laughter]**Jerod Santo:** [30:10] Just so much confidence, but wrong most of the time. [laughs]**Shawn Wang:** Exactly. Which happens to Galactica, which is this sort of science LLM from Meta, where Yann LeCun, who is one of the big names in tech, was like "This thing will generate papers for you." And within three days, the internet tore it apart, and they had to take it down. It was a very, very dramatic failure, this kind of tech... Because you're talking about biology, and science, and medicine, and you can't just make stuff up like that. [laughs]**Jerod Santo:** Right. So like in the world where chat GPT operates today, which is really in the world of fiction, and kind of BS-ing, for lack of a better term, like writing intros to a podcast - you know, like, it doesn't have to be correct necessarily; it can be like close enough to correct, and then you can massage it, of course, you can cherry pick to get the one that you like... But when the rubber hits the road, like on serious things, like science, or "How many of these pills do I need to take?" I guess that is also -- that's health science. So science, and other things... It's like, it can't be correct 60% of the time, or 80%, or even like 95%. It's gotta reach that point where you actually can trust it. And because we're feeding it all kinds of information that's not correct, de facto... Like, how much of the internet's wrong? Most of it, right?**Adam Stacoviak:** I mean, medicine though has evolved too, and it hasn't always been correct, though it's also very serious... You'd get advice from a doctor 10-15 years ago, they'd say it with full confidence and full accuracy, but it's only based on that current dataset.**Jerod Santo:** But you can sue them for malpractice and stuff, right? Like, how do we take recourse against--**Adam Stacoviak:** You can if they actually have malpractice; they can be wrong, because it's as much science as possible to make the most educated guess. It's malpractice when there's negligence; it's not malpractice when they're wrong.**Jerod Santo:** A good doctor will actually go up to the fringe and say, "You know what - I'm not 100% sure about this. It's beyond my knowledge."**Adam Stacoviak:** Sure. For sure.**Jerod Santo:** "Here's what you can do. Here's the risks of doing that." Whereas the chat bots, the ChatGPT thing is like, "The answer is 7", and you're like, "It actually was 12." And it's like, "Ah, shoot..." [laughter]**Adam Stacoviak:** Well, I think when there's mortality involved, maybe there's going to be a timeframe when we actually begin to trust the future MedGPT, for example; I don't know if that's a thing in the future, but something that gives you medical results or responses based upon data, real data, potentially, that you get there, but it's not today.**Jerod Santo:** Well, I think this goes back to the data point that you made, and I think where we go from like the 95 -- I'm making up numbers here, but like 95% accuracy, to get it to like 98.5%, or 99%. Like, that's gonna require niche, high-value, high-signal data that maybe this medical facility has, because they've been collecting it for all these years. And they're the only ones who have it. And so maybe that's where you like carve out proprietary datasets that take these models from a baseline of accuracy, to like, in this particular context of health it's this much accuracy. And then maybe eventually you combine all those and have a super model. I don't know... Swyx, what do you think?**Shawn Wang:** I love the term super-model. I think the term [unintelligible 00:33:23.10] in the industry is ensemble. But that just multiplies the costs, right? Like if you want to run a bank of five models, and pick the best one, that obviously 6x-es your cost. So not super-interesting; good for academic papers, but not super-interesting in practice, because it's so expensive.There's so many places to go with this stuff... Okay, there's one law that I love, which is Brandolini's Law. I have this tracking list of eponymous laws... Brandolini's law is people's ability to create bulls**t far exceeds the ability of people to refute it. Basically, if all of these results of this AI stuff is that we create better bulls***t engines, it's not great. And what you're talking about, the stuff with like the 90% correct, 95% correct - that is actually a topic of discussion. It's pretty interesting to have the SRE type conversation of "How many nines do you need for your use case, and where are we at right now?" Because the number of nines will actually improve. We are working on -- sorry, "we" as in the collective human we, not me personally...**Adam Stacoviak:** [34:32] The royal we, yes.**Shawn Wang:** The role royal we... Like, humanity is working on ways to improve, to get that up. It's not that great right now, so that's why it's good for creativity and not so much for precision, but it will get better. One of the most viral posts on Hacker News is something that you featured, which is the ability to simulate virtual machines instead of ChatGPT-3, where people literally opened -- I mean, I don't know how crazy you have to be, but open ChatGPT-3, type in LS, and it gives you a file system. [laughter]**Jerod Santo:** But that only exists -- it's not a real file system, it's just one that's [unintelligible 00:35:00.05]**Shawn Wang:** It's not a real file system, for now. It's not a real set file system for now, because they hallucinate some things... Like, if you ask it for a Git hash, it's gonna make up a Git hash that's not real, because you can verify [unintelligible 00:35:10.25] MD5. But like, how long before it learns MD5? And how long before it really has a virtual machine inside of the language model? And if you go that far, what makes you so confident that we're not in one right now? [laughs]**Jerod Santo:** Now I'm uncomfortable... That actually is a very short hop into the simulation hypothesis, because we are effectively simulating a brain... And if you get good enough at simulating brains, what else can you simulate?**Adam Stacoviak:** What else WOULD you want to simulate? I mean, that's the Holy Grail, a brain.**Shawn Wang:** Yeah. So Emad Mostaque is the CEO of Stability AI. He's like, "We're completely unconcerned with the AGI. We don't know when it'll get here. We're not working on it. But what we're concerned about is the ability to augment human capability. People who can't draw now can draw; people who can't write marketing texts or whatever, now can do that." And I think that's a really good way to approach this, which is we don't know what the distant future is gonna hold, but in the near future, this can help a lot of people.**Adam Stacoviak:** It's the ultimate tool in equality, right? I mean, if you can do --**Shawn Wang:** Yeah, that's a super-interesting use case. So there was a guy who was like sort of high school-educated, not very professional, applying for a job. And what he used ChatGPT to do was like "Here's what I want to say, and please reward this in a professional email." And it basically helped to pass the professional class status check. Do you know about the status checks? All the other sort of informal checks that people have, like "Oh, we'll fly you in for your job interview... Just put the hotel on your credit card." Some people don't have credit cards. And likewise, when people email you, you judge them by their email, even though some haven't been trained to write professionally, right? And so yeah, GPT is helping people like that, and it's a huge enabler for those people.**Adam Stacoviak:** Hmm... That is -- I mean, I like that idea, honestly, because it does enable more people who are less able... It's a net positive.**Shawn Wang:** Yeah. I mean, I seem generally capable, but also, I have RSI on my fingers, and sometimes I can't type. And so what Whisper is enabling me to do, and Copilot... So GitHub, at their recent GitHub Universe, recently announced voice-enabled Copilot... And it is good enough for me to navigate VS Code, and type code with Copilot and voice transcription. Those are the two things that you need; and they're now actually good enough that I don't have to learn a DSL for voice coding, like you would with Talon, or the prior solutions.**Adam Stacoviak:** You know, it's the ultimate -- if you're creative enough, it's almost back to the quote that Sam had said, that you liked... Well, I'm gonna try and go back to it; he says "At the end, because they were just able to articulate it with a creative eye that I don't have." So that to me is like insight, creativity; it's not skill, right? It's the ability to dream, which is the ultimate human skill, which is - since the beginning of time, we've been dreamers.**Shawn Wang:** [38:01] This is a new brush. Some artists are learning to draw with it. There'll be new kinds of artists created.**Adam Stacoviak:** Provided that people keep making the brush, though. It's a new brush...**Shawn Wang:** Well, the secret's out; the secret's out that you can make these brushes.**Jerod Santo:** Right.**Adam Stacoviak:** Yeah, but you still have to have the motivation to maintain the brush, though.**Jerod Santo:** What about access, too? I mean, right now you're talking about somebody who's made able, that isn't otherwise, with let's just say ChatGPT, which is free for now. But OpenAI is a for profit entity, and they can't continue to burn money forever; they're gonna have to turn on some sort of a money-making machine... And that's going to inevitably lock some people out of it. So now all of a sudden, access becomes part of the class, doesn't it? Like, you can afford an AI and this person cannot. And so that's gonna suck. Like, it seems like open source could be for the win there, but like you said, Swyx, there's not much moving and shaking in that world.**Adam Stacoviak:** Well, I haven't stopped thinking about what Swyx said last time we talked, which was above or below the API, which is almost the same side of the coin that we talked about last time, which is like, this the same thing.**Jerod Santo:** Yeah. Well, ChatGPT is an API, isn't it?**Shawn Wang:** Nice little callback. Nice. [laughter]**Adam Stacoviak:** I really haven't been able to stop thinking about it. Every time I use any sort of online service to get somebody to do something for me that I don't want to do, because I don't have the time for it, or I'd rather trade dollars for my time, I keep thinking about that above or below the API, which is what we talked about. And that's what Jerod has just brought up; it's the same exact thing.**Shawn Wang:** Yep, it is. One more thing I wanted to offer, which is the logical conclusion to generative. So that post where we talked about why prompt engineering is overrated - the second part of it is why you shouldn't think about this as generative... Because right now, the discussion we just had was only thinking about it as a generative type of use case. But really, what people want to focus on going forward is -- well, two things. One is the ability for it to summarize and understand and reason, and two, for it to perform actions. So the emerging focuses on agentic AI; AI agents that can perform actions on your behalf. Essentially, hooking it up to -- giving it legs and legs and arms and asking it to do stuff autonomously.So I think that's super-interesting to me, because then you get to have it both ways. You get AI to expand bullet points into prose, and then to take prose into bullet points. And there's a very funny tweet from Josh Browder, who is the CEO DoNotPay, which is kind of like a --**Adam Stacoviak:** Yeah, I'm a fan of him.**Shawn Wang:** Yeah. Fantastic, right? So what DoNotPay does is they get rid of annoying payment UX, right? Like, sometimes it was parking tickets, but now they are trying to sort of broaden out into different things. So he recently tweeted that DoNotPay is working on a way to talk to Comcast to negotiate your cable bill down. And since Comcast themselves are going to have a chat bot as well, it's going to be chat bots talking to each other to resolve this... [laughter]**Adam Stacoviak:** Wow, man...**Jerod Santo:** It's like a scene out of Futurama, or something...**Shawn Wang:** Yeah. So I'm very excited about the summarization aspects, right? One of the more interesting projects that came out of this recent wave was Explained Paper, which is - you can throw any academic paper at it and it explains the paper to you in approachable language, and you can sort of query it back and forth. I think those are super-interesting, because that starts to reverse Brandolini is law. Instead of generating bulls**t, you're taking bulls**it in, getting into some kind of order. And that's very exciting.**Adam Stacoviak:** Yeah. 17 steps back, it makes me think about when I talk to my watch, and I say "Text my wife", and I think about like who is using this to their betterment? And I'm thinking like, we're only talking about adults, for the most part. My kid, my son, Eli - he talks to Siri as if like she knows everything, right? But here's me using my watch to say "Text my wife." I say it, it puts it into the phone... And the last thing it does for me, which I think is super-interesting for the future, as like this AI assistant, is "Send it" is the final prompt back to me as the human; should I send this? And if I say no, Siri doesn't send it. But if I say "Send it", guess what she does? She sends it. But I love this idea of the future, like maybe some sort of smarter AI assistant like that. I mean, to me, that's a dream. I'd love that.**Shawn Wang:** [42:21] Yeah, I was watching this clip of the first Iron Man, when Robert Downey Jr. is kind of working with his bot to work on his first suit... And he's just talking to the bot, like "Here's what I want you to do." Sometimes it gets it wrong and he slaps it on the ahead... But more often than not, he gets it right. And this is why I've been -- you know, Wes Boss recently tweeted -- this is actually really scary. "Should we be afraid as engineers, like this is going to come for our jobs?" And I'm like, "No. All of us just got a personal junior developer." That should excite you.**Jerod Santo:** Yeah. And it seems like it's particularly good at software development answers. You'd think it's because there's lots of available text... I mean, think about like things that it's good at; it seems like it knows a lot about programming.**Shawn Wang:** I have a list. Do you want a list?**Jerod Santo:** Yeah.**Shawn Wang:** So writing tutorials - it's very good. Literally, tables of contents, section by section, explaining "First you should npm install. Then you should do X. Then you should do Y." Debugging code - just paste in your error, and paste in the source code, and it tells you what's wrong with it. Dynamic programming, it does really well. Translating DSLs. I think there'll be a thousand DSLs blooming, because the barrier to adoption of a DSL has just disappeared. [laughs] So why would you not write a DSL? No one needs to learn your DSL.**Adam Stacoviak:** What is this, Copilot you're using, or ChatGPT, that you're--**Shawn Wang:** ChatGPT-3. I have a bunch of examples here I can drop in the show notes. AWS IAM policies. "Hey, I want to do X and Y in AWS." Guess what? There's tons of documentation. ChatGPT knows AWS IAM policies. Code that combines multiple cloud services. This one comes from Corey Quinn. 90% of our jobs is hooking up one service to another service. You could just tell it what to do, and it just does it, right? There a guy who was like, "I fed my college computer network's homework to it, and they gave the right result", which is pretty interesting.Refactoring code from Elixir to PHP is another one that has been has been done... And obviously, Advent of Code, which - we're recording this in December now. The person who won -- so Advent of Code for the first 100 people is a race; whoever submits the correct answer first, wins it. And the number one place in the first Advent of Code this year was a ChatGPT guy. So it broke homework. Like, this thing has broken homework and take-home interviews, basically. [laughs]**Jerod Santo:** Completely. It's so nice though; like, I've only used it a little bit while coding, but it's two for two, of just like drilling my exact questions. And just stuff like "How do you match any character that is not an [unintelligible 00:44:43.28] regular expression?"**Shawn Wang:** Oh, yeah. Explaining regexes.**Jerod Santo:** Yeah. That was my question. Like, I know exactly what I want, but I can't remember which is the character, and so I just asked it, and it gave me the exact correct answer, and an example, and explained it in more detail, if I wanted to go ahead and read it. And it warned me, "Hey, this is not the best way to test against email addresses... But here it is." So I was like, "Alright..." This is a good thing for developers, for sure.**Shawn Wang:** Yeah. But you can't trust it -- so you have a responsibility as well. You can't write bad code, have something bad happen, and go, "Oh, it wasn't my fault. It was ChatGPT."**Jerod Santo:** Well, you can't paste Stack Overflow answers into your code either.**Shawn Wang:** You have the responsibility. Exactly.**Jerod Santo:** Yeah. I mean, you can, but you're gonna get fired, right? Like, if the buck stops at you, not at the Stack Overflow answer person, you can't go find them and be like, "Why were you wrong?" Right? It stops at you.**Shawn Wang:** Yeah. So I think the way I phrased it was -- do you know about this trade offer meme that is going around? So it's "Trade offer - you receive better debugging, code explanation, install instructions, better documentation, elimination of your breaking of flow from copy and pasting in Stack Overflow - you receive all these benefits, in exchange for more code review." There is a cost, which is code review. You have to review the code that your junior programmer just gave you. But hey, that's better and easier than writing code yourself.**Jerod Santo:** [46:04] Yeah, because you've got a free junior programmer working for you now. [laughter]**Shawn Wang:** There's a guy that says, "I haven't done a single Google search or consulted any external documentation for the past few days, and I was able to progress faster than I ever had when delivering a new thing." I mean, it's just... It's amazing, and Google should be worried.**Jerod Santo:** Yeah, that's what I was gonna say - is this an immediate threat to Google? Now, I did see a commenter on Hacker News - Swyx, I'm not sure if you saw this one - from inside of Google, talking about the cost of integration?**Shawn Wang:** Yes. Yeah, I've read basically every thread... [laughter] Which is a full-time job, but... This is so important. Like, I don't do this for most things, right? Like, I think this is big enough that I had to drop everything and go read up on it... And not be an overnight expert, but at least try to be informed... And that's all I'm doing here, really. But yeah, do you want to read it up?**Jerod Santo:** Yeah. So in summary, they were responding... This is on a thread about ChatGPT, and they say -- this is a Googler, and they say "It's one thing to put up a demo that interested nerds can play with, but it's quite another thing to try to integrate it deeply in a system that serves billions of requests a day, when you take into account serving costs, added latency, and the fact that average revenue on something like a Google search is close to infinitesimal (which is the word I can't say out loud) already. I think I remember the presenter saying something like they'd want to reduce the cost by at least 10 times before it could be feasible to integrate models like this in products like Google search. A 10x or even 100x improvement is obviously an attainable target in the next few years, so I think technology like this is coming in the next few years."So that's one insider's take on where Google stands. Obviously, Google has tons of resources dedicated to these areas of expertise, right? It's not like Google's asleep at the wheel, and is going to completely have their lunch eaten by OpenAI. But right now, there's a lot of people who are training new habits, right? They're like, "I'm not gonna use Google anymore. I'm gonna start using OpenAI." I think it's something on the order of one million users in their first few days have signed up... How long can Google potentially bleed people before it becomes an actual problem? I don't know. I don't know the answer to these things.**Shawn Wang:** So there's one way in which you can evaluate for yourself right now, and I think that's the most helpful, constructive piece of advice that we can give on this podcast, which is -- we're covering something that is moving very live, very fast. Everything that we say could be invalidated tomorrow by something new. But you could just run ChatGPT-3 alongside of all your Google searches. That's a very, very simple way to evaluate if this would replace Google for you; just run it twice, every single time. And so there's a Google extension - and I'll link it - [unintelligible 00:48:47.04] ChatGPT Google extension; I'll put it in the show notes. And yeah, I have it running; it's not that great. [laughs] Surprisingly. So ChatGPT is optimized for answering questions. Sometimes I don't put questions in there. I just put the thing I'm looking for, and Google's pretty good at that, it turns out... [laughs]**Jerod Santo:** Right. See, because you are an expert-level Google prompt engineer, right? Like, you know how to talk to Google.**Shawn Wang:** We have optimized to Google prompting, yes.**Jerod Santo:** Exactly.**Shawn Wang:** If I need to search within a certain date range, I know how to do that in Google. I can't do that in ChatGPT-3. If I need to look for PDFs, I know how to do that. If I want to look for Reddit, and constrain the site to Reddit, I know how to do that. ChatGPT-3 has no concept of attribution, no concept of date ranges, and stuff like that.**Jerod Santo:** Right.**Shawn Wang:** But yeah, it is just like better at some things, and worse at other things, and that is the nature of all new technology. It just has to be better at one thing, that you cannot get anywhere else, and it has a permanent hold in your mind. Whenever you need that thing done, you will turn to ChatGPT-3, or any other new technology.[49:53] I love this sort of meta philosophy about technology adoption, because all new toys just generally are worse than the things that they replace, except in one area, and that's the area needs to matter. And if it does matter, it will win, because they will fix the bugs.**Jerod Santo:** Yeah, oftentimes with disruption, that area is cost; like acquisition cost. Sometimes it's convenience, and maybe I guess sometimes it's accuracy. There's different metrics, but it's got to be the one that matters. If it's marginally better at things that don't matter, you're not going to disrupt. But if it's a lot better at one thing that matters a lot, even if everything else sucks, you'll use that thing.**Shawn Wang:** Yeah, exactly. So it's interesting, because -- you know, Google has a few things going for it. By the way, it has one of the largest training repositories of text that no one else has, which is Gmail. But the most impressive thing it's being able to ship with Gmail is the little autocomplete, like, "Looks good", Okay", the little buttons that you see in the smart replies.**Jerod Santo:** Do you guys ever use those? Do you ever click on those?**Shawn Wang:** I use that. I use that. Save some typing.**Adam Stacoviak:** Yeah, well, I used to actually use Gmail directly to compose my emails, or respond. I would tap to complete all the time, if the response was like, "Yeah, I was gonna say that."**Shawn Wang:** There's a billion little ways that AI is built into Google right now, that we just take for granted, because we don't feel it, because there's no prompts. [laughter]**Jerod Santo:** We need a prompt!**Adam Stacoviak:** Even if OpenAI did eat Google's lunch, Google would just acquire it, or something...**Shawn Wang:** You would think so...**Jerod Santo:** Maybe...**Shawn Wang:** But I would say that probably OpenAI is not for sale. Like, they have this world-conquering ambition that would just not let them settle for anything less than global domination... Which is a little bit scary, right?**Jerod Santo:** Yeah, I think they're probably going the distance, is their plan, it seems like...**Shawn Wang:** Well, if anything, Microsoft should have bought them when they had the chance, because that was Bing's opportunity, and I don't think that ever came to pass... Probably because Sam Altman was smart enough not to do that deal. But yeah, so let's take that line of thinking to its logical conclusion. What would you feel if Google started autocompleting your entire email for you, and not just like individual, like two or three words? You would feel different, you would feel creeped out. So Google doesn't have the permission to innovate.**Adam Stacoviak:** I wouldn't freak out if I opted in, though. If I was like, "This technology exists, and it's helpful. I'll use that." Now, if it just suddenly started doing it, yeah, creeped out. But if I'm like, "Yeah, this is kind of cool. I opt into this enhanced AI, or this enhanced autocompletion", or whatever, simplifies the usage of it, or whatever.**Shawn Wang:** Yeah, so there's actually some people working on the email client that does that for you. So Evan Conrad is working on EveryPrompt email, which is essentially you type a bunch of things that you want to say, and you sort of batch answer all your emails with custom generated responses from GPT-3. It's a really smart application of this tech to email that I've seen. But I just think, like, you would opt in; the vast majority of people never opt into anything.**Jerod Santo:** Yeah, most people don't opt in.**Shawn Wang:** Like, that's just not the default experience. So I'm just saying, one reason that Google doesn't do it is "Yeah, we're just too big." Right? That is essentially the response that you read out from that engineer; like, "This doesn't work at Google scale. We can't afford it. It would be too slow", whatever. That's kind of a cop out, I feel like... Because Google should be capable. These are the best engineers in the world, they should they should be able to do it.**Jerod Santo:** Well, he does say he thinks it's coming in the next few years. So he's not saying it's impossible, he's saying they're not there yet. And I will say, I'm giving ChatGPT the benefit of my wait time that I do not afford to Google. I do not wait for Google to respond. I will give ChatGPT three to five seconds, because I know it's like a new thing that everyone's hitting hard... But like, if they just plugged that in, it would be too slow. I wouldn't wait three to five seconds for a Google search.**Shawn Wang:** Yeah. By the way, that's a fascinating cloud story that you guys have got to have on - find the engineer at OpenAI that scaled ChatGPT-3 in one week from zero to one million users?**Jerod Santo:** Yeah, totally.**Adam Stacoviak:** [53:58] Well, if you're listening, or you know the person, this is an open invite; we'd love to have that conversation.**Shawn Wang:** Yeah. I've seen the profile of the guy that claimed to [unintelligible 00:54:04.00] so that he would know... But I don't know who would be responsible for that. That is one of the most interesting cloud stories probably of the year. And Azure should be all over this. Azure should be going like, "Look, they handled it no problem. This is most successful consumer product of all time come at us", right?**Jerod Santo:** That's true. They should.**Shawn Wang:** They're the number three cloud right now. This is like their one thing, this is their time to shine. They've got to do it.**Jerod Santo:** And does anybody even know that Azure is behind OpenAI? I'm sure you can find out, but like, is that well known? I didn't know that.**Shawn Wang:** Oh, it's very public. Microsoft invested a billion dollars in OpenAI.**Jerod Santo:** Okay. Did you know that, Adam?**Adam Stacoviak:** No.**Jerod Santo:** So I'm trying to gauge the public knowledge...**Shawn Wang:** What we didn't know was that it was at a valuation of $20 billion, which... So OpenAI went from like this kind of weird research lab type thing into one of the most highly valued startups in the world. [laughs]**Jerod Santo:** Do you think Microsoft got their money's worth?**Shawn Wang:** I think so... It's awash right now, because --**Jerod Santo:** Too early.**Shawn Wang:** ...they probably cut them a lot of favorable deals for training, and stuff... So it's more about like being associated with one of the top AI names. Like, this is the play that Microsoft has been doing for a long time, so it's finally paying off... So I'm actually pretty happy for that. But then they have to convert into like getting people who are not [unintelligible 00:55:21.00] onto this thing.**Break:** [55:26]**Adam Stacoviak:** What's the long-term play here though? I mean, if Microsoft invested that kind of money, and we're using ChatGPT right now, we're willing to give it extra seconds, potentially even a minute if the answer is that important to you, that you wouldn't afford to Google... Like, what's the play for them? Will they turn this into a product? How do you make billions from this? Do you eventually just get absorbed by the FAANGs of the world, and next thing you know now this incredible future asset to humanity is now owned by essentially folks we try to like host our own services for? Like, we're hosting Nextcloud locally, so we can get off the Google Drives and whatnot... And all this sort of anti-whatever. I mean, what's the endgame here?**Shawn Wang:** Am I supposed to answer that? [laughs]**Adam Stacoviak:** Do you have an answer? I mean, that's what I think about...**Jerod Santo:** Let's ask ChatGPT what the endgame is... No, I mean, short-term it doesn't seem like OpenAI becomes the API layer for every AI startup that's gonna start in the next 5 or 10 years, right? Like, aren't they just charging their fees to everybody who wants to integrate AI into their products, pretty much? That's not an end game, but that's a short-term business model, right?**Shawn Wang:** That is a short-term business model, yeah. I bet they have much more up their sleeves... I don't actually know. But they did just hire their first developer advocate, which is interesting, because I think you'll start to hear a lot more from them.[58:12] Well, there's two things I will offer for you. One, it's a very common view or perception that AI is a centralizing force, right? Which is, Adam, what you're talking about, which is, "Does this just mean that the big always get bigger?" Because the big have the scale and size and data advantage. And one of the more interesting blog posts - sorry, I can't remember who I read this from - was that actually one of the lessons from this year is that it's not necessarily true, because AI might be a more decentralized force, because it's more amenable to open source... And crypto, instead of being decentralized, turned out to be more centralized than people thought.So the two directions of centralized versus decentralized - the common perception is that AI is very centralized, and crypto very decentralized. The reality was that it's actually the opposite, which is fascinating to me as a thesis. Like, is that the end game, that AI eventually gets more decentralized, because people want this so badly that there are enough researchers who go to NeurIPS to present their research papers and tweet out all this stuff, that diffuses these techniques all over the place? And we're seeing that happen, helped in large probably by Stability AI. The proof that Stability as an independent, outsider company, like not a ton of connections in the AI field, did this humongous achievement I think is just a remarkable encouragement that anyone could do it... And that's a really encouraging thing for those people who are not FAANG and trying to make some extra headroom in this world. So that's one way to think about the future.The second way to think about who monetizes and who makes the billion dollars on this... There's a very influential post that I was introduced to recently from Union Square Ventures, called "The myth of the infrastructure phase", which is directly tackling this concept that everyone says "When you have a gold rush, sell picks and shovels", right? And it's a very common thing, and presumably AI being the gold rush right now, you should sell picks and shovels, which is you should build AI infrastructure companies. But really, there are tons of AI infrastructure companies right now, they're a dime a dozen; really, they're all looking for use cases, and basically, the argument, the myth of the infrastructure phase is that technology swings back and forth between app constraint and infra constraint. And right now, we're not infrastructure-constrained, we're app-constrained. And really, it's the builders of AI-enabled products like TikTok that know what to do with the AI infrastructure tha

Nick Hodge, Co-Owner of Digest Publishing and editor of Foundational Profits and Hodge Family Office, joins us for a wide-ranging discussion recapping the macroeconomic environment in 2022, and the factors driving various market sector trends heading into 2023.  This is a wide-ranging discussion getting into the US Dollar, interest rates, general US equities, Gold, Oil, battery metals, cryptocurrencies, home prices, and much more.  We dig in a bit more to the pitfalls in some newer investors market psychology within the current bear market in general US equities, and global equity markets.  Nick discusses what kinds of signals to look out for in the event of a larger capitulation event.    With the ongoing pressure on the wealth effect in investors portfolios and in home prices, coupled with cracks under the surface in the labor markets, we then discuss the nuances of this stagflation environment and how we are likely mid-way through an evolving recession.  Next we review the recent crypto crash, and whether or not the “crypto soldiers are in fact training to be in the gold army.”  We wrap up with a look forward into next year, where Nick still sees weakness in tradition tech stocks and the FAANGS, but is more constructive on consumer staples, utilities, gold, and energy metals like lithium, uranium, and helium with strong fundamental drivers.    

It's our 200th episode of the Money and Markets podcast. To celebrate we have three special guests talking about things that really matter to savers and investors. Laura Suter chats to NS&I chief executive Ian Ackerley about premium bonds and savings rates. Dan Coatsworth talks to Polar Capital Technology Trust manager Ben Rogoff about the change in fortunes for tech stocks. Dan asks Ben whether it is time for the Faangs to be relegated and a new group of tech stocks to lead the pack. They also talk about opportunities in the sector following widespread share price declines. Artemis fund manager Rebecca Young explains why investors with a 60/40 equity/bond portfolio shouldn't panic about the bond component failing to provide support this year. Laith Khalaf looks at the latest activities among equities, currencies and government bonds, while Dan explains why the potential sale of Manchester United football club matters to investors, and why Disney has brought back its old chief executive.

Joel Elconin, Co-Host of the Benzinga PreMarket Prep Show and Editor of the PreMarket Prep website, joins us to discuss the continued rally in equities, and the rotation trade out of sector leading FAANG stocks, and the importance of diversification in one's portfolio.   We start off by recapping the market take on the recent CPI and PPI inflation data from the last 2 weeks, and how this shifted expectations for Fed policy moving forward.   Next we shift over to the retail sector, and how Walmart raised the bar for the holiday season, on to have Target dash those dreams shortly thereafter, with many other stocks following a similar pattern of a big pop, followed by a drop.   The discussion then gets into the huge valuation mismatches still seen in many of the tech and growth stocks, only compounded by this recent rally in many sectors and stocks.  We postulate that after this there may be a rotation out of the FAANG stocks, and into other market sectors, as investors seek new leadership in many indexes. We wrap up by getting the technical levels and trajectory that Joel is looking at as far as the cryptocurrencies.

Over the last 10 years, FAANG stocks — Facebook, Amazon, Apple, Netflix and Google — dominated the investor landscape, with a disproportionate influence over the S&P 500's growth. That's all changed now, says Philip Petursson, Chief Investment Strategist for IG Wealth Management. In 2022, FAANGs are no longer super growers, they're mature giants, and valuation matters once more.

After the results, are any FAANGs worth buying? FAANGs, a mixed bag with Meta (NASDAQ code: META) the biggest loser. Is it worth buying or what of the other FAANGs? Apple (NASDAQ share code: AAPL) and Amazon (NASDAQ code: AMZN) would be my picks. Why buy the losers? Simon Shares RMI, I got confused between RMI and RMH last week. Former is becoming Outsurance. Capital & Counties (JSE code: CCO) trading update shows strong leasing activity at Covenant Garden. Octodec (JSE code: OCT) results, discout to NAV +50%, dividend yield ±14%. Sasol (JSE code: SOL) convertible bond issue essential a back door right issue. Bonds expire in five years and convert into Sasol shares at US$20.3863. RSA Retail Savings bonds now offer 11.5% fixed for five years.

Henry Biddlecombe – Co-manager: BCI Global Technology Fund, Anchor Capital

C19 "Facism" defined @hfrfromthefloor says business #climatechange well on its way lower in Euro land $EWG FAANGS making new lows but for $AAPL $FB $GOOG MSFT 0.00 $CL_F green for day $ZB_F smashed no buyers still in sight. Market feels heavy, trading skiddish

No Paul this week – it's another round of Playing FTSTEVE! On this week's show, we're talking about Adobe, Ethereum, stocks we'd like to buy, and the new FAANG stocks. We're kicking off with some impromptu news about Ethereum. There's a merge going on. What's happening and what does it mean for stocks? Steve D has the news and Steve W is thinking about Nvidia… Next is the new FAANGs. Steve W's been reading something from the Bank of America talking about the new leadership in stocks for a low-growth, high inflation world. What makes the list? And do the Steves prefer FAANG 2.0, or the original recipe? We also have news from Adobe. The stock is down quite a bit since news of its acquisition of rival Figma was announced. Steve D's been looking at this one -- $20bn sounds like a lot, especially since half of it is coming in Adobe's stock. Lastly, it's stocks that we've got our eyes on. Steve D is looking at a European stock with a dominant position in aesthetic dentistry. Steve W has been checking out a FTSE 250 industrial distribution outfit. These aren't for Paul, but could they be for you..? Only on this week's PlayingFTSE!

In recent weeks, the BizNews tribe has been subjected to strong opinions on why 'Value' stocks are about to enjoy a massive re-rating - and high flyers of the past few years set to fall even further after the recent 30% correction. London-based Mark Perchtold presents the counter view, arguing that concerns about inflation running riot are overdone and as a result, that it is time to start accumulating beaten-down Big Tech stocks. The cornerstone of his mindset is a view that technological advances, population growth and benefits of globalisation will continue to exert a powerful influence on price increases. And as a result, that once aberrations like supply chain blockages, interest rate hikes and the Ukraine War are behind us, the world will return to a place where deflation, rather than inflation, is a more likely danger. He spoke to Alec Hogg of BizNews. Learn more about your ad choices. Visit megaphone.fm/adchoices

In today's conversation engineer Harsh Mittal shares what its like to work at Microsoft, the differences between interviewing at Microsoft and Amazon, and a 9-step plan to approach the software engineer interview. Talk with Harsh here —> https://app.carrus.io/s/harsh-mittalYou can also hear a more detailed breakdown of his 9-step approach here: https://www.youtube.com/watch?v=vTVAfjFWvOo&t=10sAt Microsoft, he worked on projects responsible for the overall quality of hardware that goes into production. He's also  the go-to person for the quick "one week crash course on becoming an expert at the subject" since his school days. He "teaches the way I feel I should've been taught." and believes that everyone deserves to fall in love with the subject they are inquisitive about.Show notes and highlights: [4:40] Harsh's transition from Microsoft to Amazon[6:48] The recruitment process out of college for Microsoft roles[8:27] Differences between Microsoft and Amazon interviews [10:43] The Microsoft culture[20:10] The talent movement between Microsoft and other FAANG companies[26:50] Harsh's 9-Step Plan for nailing engineering interviews[46:00] The trend of companies outsourcing their technical interview screeningQuestions, comments or feedback? I'd love to hear from you. Email me at misha@carrus.io!

Another night of deep red on Wall Street last night and another night of gold and silver price strength in the face of it. Markets were rocked by the surprise rate hike of 50bps by the Swiss National Bank but more particularly the expected sell off of their mountain of US shares, particularly the ultra vulnerable FAANGs they've gone heavy on. The NASDAQ ended the session down 4.1%. But it wasn't the Swiss alone. More broadly we are seeing a set up mirroring the huge gold rallies of the 70's and 2000's.

Large technology companies are often grouped together due to their assumed similarities. However, the shortcomings of this type of broad categorisation were laid bare throughout the COVID-19 pandemic, with the difference between the best and worst performing share price in this group being more than 100% over the last two years. In this radio interview, Victor Mupunga, Senior Research Analyst at Private Client Securities explains that, with widely divergent prospects and facing different risks, it is important that investors clearly differentiate between individual companies. 

With many of the largest tech stocks falling over 20% year-to-date, is now the time to invest? Has the market changed to where tech investing is a safe bet?Topics covered include:What happened to NetflixWhat contributed to the astounding performance of large tech stocks since 2013How the largest contributors to overall stock market performance are always changingWhy the largest tech companies could fall even more from today's levelWhat are the valuations and sentiment toward large tech stocksWhat is complexity economics and how does it influence technologyHow younger investors and fractional trading have influenced the stock marketWhy stock splits are less effective today in driving up share pricesFor more information on this episode click here.SponsorsPolicygenius - save over 50% on life insuranceOurCrowd - the fastest-growing venture capital communityShow NotesNetflix stock plunges as subscribers quit by Julianne Pepitone and Aaron Smith—CNN MoneyNetflix Explores a Version With Ads as Subscriber Base Shrinks by Joe Flint and Denny Jacob—The Wall Street JournalNo, you did not see the Netflix mess coming by Robert Armstrong—Financial TimesFANMAG: Because FAANGs Are So Yesterday—DimensionalComplexity and the Economy by W. Brian ArthurRising Risk of Stagflation by Chris Brightman—Research Affiliates"Fractional Trading" by Zhi Da, Vivian W. Fang, and Wenwei Lin"Attention Induced Trading and Returns: Evidence from Robinhood Users" by Brad M. Barber, Xing Huang, Terrance Odean, and Christopher SchwarzRetail Raw: Wisdom of the Robinhood Crowd and the COVID Crisis by Ivo Welch (NBER Working Paper No. 27866. September 2020, Revised October 2020)—National Bureau of Economic ResearchFor more information on this episode click here.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Stagflation is here: GDP is shrinking while prices continue to rise.  Fed has no choice but to keep raising rates and stocks are responding normally to this, by tanking (Friday was brutal). The FAANG stocks in particular have stopped propping up the market. They led the market up and now they're leading it down. The sign of a true leader. Housing affordability is at the worst level ever. Higher rates and higher prices must cause the housing market to slow down. The recession is already here. The understating of the inflation rate has hidden real negative GDP growth over the past 2-3 quarters. US government responds to Musk buying Twitter by launching a Ministry of Truth -- housed in Homeland Security and run by a cartoon villain.  Russia/Ukraine war is settling into a quagmire AND getting even more dangerous as Nato sends more weapons. This is clearly a Nato operation to weaken Russia.  But it might backfire on the dollar.

Cracks seem to be appearing in Covid winners, as the sensitivity to earnings/guidance misses has grown, as exhibited by strong price declines for more "innovative" market darlings. These companies have a high likelihood of falling into the "overearning" camp, where expectations may be far too high, thus pull forward risk is underappreciated for the quality and durability of earnings growth in the future. They appear all offence and no defence! Investors shouldn't overlook the potential benefits of focusing on the "underearning" camp, particularly companies in the energy sector, where earnings are likely to be far higher and of better quality than market participants may be giving them credit for. It looks like what's "old" will be "new" again, and those investors and managers that are lacking energy may find themselves left out in the cold. - Rajiv Jain, GQG Partners. Earn 0.50 CE/CPD hrs on Portfolio Construction Forum

This week, it's a big week for tech - and not only thanks to Elon Musk's bid to buy Twitter. The FAANGs will each have reported by the time the week is out and investors will know much better how the largest companies in the world are getting on.   See omnystudio.com/listener for privacy information.

Stocks generally perform better than cash in inflationary environments.FAANGs in the global economy.Brightest minds and innovation. The global talent pool. Learning from leading minds. 

In this episode, Dave and Jamison answer these questions: I wanted to know if listing past offers (as a brand name signal) on your resume will help or hurt you during the resume screening and interview stages? I am an SQA engineer at one of the FAANGS, and I feel inadequate in my position; I get the gist QAs are not valued much. Essentially I got into this domain early in my career, and I find moving out of this role difficult. My long-term goal is to get into a PM role. Is that even possible, or should I first switch to the Dev role to build a better foundation? Help me. I am lost.

The stock-picker talks about her recent declines, why she's sticking with companies like Tesla, Zoom, and Spotify, and why her rivals are overloaded on the FAANGs. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week, Mighty Capital Founding Partner and host of the series on The Age of Product, SC Moatti, sat down with Amplitude Founding CEO, Spenser Skates to discuss how companies can compete against FAANGs (Facebook, Apple, Amazon, Netflix, and Google). Spenser Skates is the Founding CEO of Amplitude, a digital acceleration platform that recently filed to go public ーI'm proud that he's also in the Mighty Capital portfolio. Before Amplitude, he worked at DRW Trading Group as an algorithmic trader. Skates studied Bioengineering at MIT where he twice won Battlecode, MIT's largest programming competition.

DB-Jan 13,2022: In today's volatile trading environment, charts can be a clear way to make investment decisions. Katie Stockton gives her technical take on the S&P 500 (which she says will enter a corrective phase in 1-2 weeks), FAANGs, 10-year yields, and more. Find out why she suggests sticking with core longs that have the support of rising moving averages and get some actionable ideas. We'll also ask how much—if at all—fundamentals like rising inflation play into her investment decisions. Interviewed by Ash Bennington. Want to submit questions? Drop them right here on the Exchange: https://rvtv.io/3FjqrbG Learn more about your ad choices. Visit megaphone.fm/adchoices

The U.S. equity market is characterized by extreme dispersion. Virtually all the gains in the last eight years have been concentrated in six stocks: the FAANGs plus Microsoft. Strip out those six stocks, and the S&P 494's performance has been utterly mediocre, roughly equal to that of the rest of the world. Here to discuss the role that dispersion plays in fund management is Chris Davis.

It's not all about FAANGs. It's time to give small and mid-cap companies the respect they deserve.Nothing in asset management is easy, but running a global mandate for small and medium companies is tougher than most.You have a lot of companies to deal with across many jurisdictions and many have little or no analyst coverage.But it's a sector of the market that has been pretty strong over the past year.In this week's Citywire Ratings Radar show, Frank Talbot runs the rule over some of the best fund managers in the area while Nisha Long, looking head to COP-26, looks at the huge amounts of cash going into equity funds that hold the EU sustainable seal of approval.   Richard Lander and Angus Foote host while producer Lucía Garré makes it all worth listening to.

The exceptional performance of small-company stocks over the last decade has been underappreciated compared to the extraordinary performance of large-cap stocks, which have been propelled by the FAANGs. Small-cap pioneer Chuck Royce explains why small caps deserve renewed attention. WEALTHTRACK # 1815 broadcast on October 08, 2021 More info: http://wealthtrack.com/small-cap-investment-legend-chuck-royce-discusses-opportunities-in-underappreciated-small-caps/ --- Support this podcast: https://anchor.fm/wealthtrack/support

Large-cap U.S growth stocks, particularly tech stocks have been the overwhelming winners of the last decade. They now dominate the market. The top ten S&P 500 stocks, including the FAANGs, account for more than 25% of the index's total market value, a concentration that worries some market watchers because it is reminiscent of other market […]

Large-cap U.S growth stocks, particularly tech stocks, have been the overwhelming winners of the last decade. They now dominate the market. The top ten S&P 500 stocks, including the FAANGs, account for more than 25% of the index's total market value, a concentration that worries some market watchers because it is reminiscent of other market tops such as the dot-com bubble when internet stocks made up over 30% of the S&P and the credit bubble when banking stocks reached more than 20%. With the exception of short-lived spurts value stocks, small-cap stocks and international stocks have badly lagged. This week's guest believes the days of this concentrated outperformance by large-cap growth stocks are numbered and suggests some underloved and under-owned alternatives. He is financial thought leader, innovator, and investor Robert Arnott, Chairman of the Board of Research Affiliates, which he founded in 2002 as a self-described “research-intensive asset management firm that focuses on innovative products.” Among the innovations that he has pioneered is fundamental indexation: building indexes with stocks based on the size of their fundamentals, such as sales, profits, cash flow, book value, and dividends - not their stock price. Research Affiliates has created numerous fundamental indexes for a wide variety of markets and asset classes around the world. Arnott will discuss why he believes this long era of U.S. large-cap growth dominance could be coming to an end and what could take its place. WEALTHTRACK #1811 broadcast on September 10, 2021 More Info: https://wealthtrack.com/financial-thought-leader-rob-arnott-likes-buying-cheap-assets-where-he-is-finding-them-now/ AGAINST THE GODS: THE REMARKABLE STORY OF RISK by Peter Bernstein https://amzn.to/3BURwjX --- Support this podcast: https://anchor.fm/wealthtrack/support

ASEAN is gaining investor interest even as US mega-tech stocks gain to uncomfortable levels in the midst of record money printing, says Tim Mulholland, President of TJM Limited in Chicago. Image credit: Shutterstock.com

ASEAN is gaining investor interest even as US mega-tech stocks gain to uncomfortable levels in the midst of record money printing, says Tim Mulholland, President of TJM Limited in Chicago. Image credit: Shutterstock.com

BD-Aug19,2021: Real Vision senior editor Ash Bennington welcomes Tommy Thornton, founder of Hedge Fund Telemetry, to update his framework for the U.S. economy and inflation as well as his outlook for equities, bonds, and commodities. After talks of tapering coming out of the FOMC minutes released yesterday, Thornton analyzes the market's response with relatively little action in the major U.S. indices as well as the dollar's continued rise and commodities like oil and copper taking a hit. He offers his perspective on the state of antitrust concerns with the FAANGs with tech giants like Amazon's plans to open department stores and Facebook's move into the metaverse while a new antitrust suit is submitted against them by the FTC. Drop your questions for Tommy here on the Exchange: https://rvtv.io/2Xxhew2 Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's F-Bomb discusses the following: -Inflation Soaring -One decision can answer many others -Rich Barton founded two monster companies -Matthew 6:24 -Keep your investing simple -Farewell Leo Messi -The enormity of the nation's largest stocks

Welcome to What The X: a special episode to mark WhatTheFs 10th episode!!! Ten stocks that I believe will be multi-baggers, with potential to go up 10X in the next 10 years!Presenting to you my very own RAK fund :-)Why am I doing this? Some of you have asked me for tips & picks in the past...and my own portfolio has consistently beaten the s&p500 index over the last few years. WhatTheFs podcast is my weekly take on fads, films & finance in a way that makes my listeners happy, makes them money, or both, so why not share some of my secret sauce? ;-) In return, would ask you to subscribe to this podcast and also spread the word by sharing this episode in your friend & social circles. Yep, go ahead...do it now - there is a share link option on the top!For this top ten list, I have focused on growth stocks only, and in the mid-tier of market capitalization ($20-$150B mkt cap), not getting sucked into the FAANGs of the mega caps (which almost everyone owns), or dabble with the little leaguers. I have looked at industries and sectors that are in the forefront of the digital revolution, that have the potential to be much much bigger in the coming decade, and then selected the disruptors in those, the challengers that are standing up to the big boys, creating their own rules, and changing the future as we know it. I am not going into fundamental or quant analysis here but you will hear about my investing story as part of these stocks too.The stock picks are all public companies  from these Ten sectors that I believe will lead in the digital future::Digital Media/AdvertisingStreamingGamingFinTechE-commerceContent MgmtNextGen Customer EngagementSecurityHealthcare, &Biotech/GeneticsA word of caution though: these are my personal recommendations, so exercise caution, do your own research, and remember that any investment you do based on the above is at your own risk.I totally enjoyed putting this list & episode together, and hope you like it too, and benefit from it. Keen to know your reactions, any ideas, stocks or angles I have missed, and anything you would like to discuss/debate further. If you liked my new style and content, let me know, rate me, and leave me a review. Here are the links to subscribe to it on all major podcast directories, and share it with your friends...Buzzsprout: https://feeds.buzzsprout.com/1721890.rssApple Podcasts:https://podcasts.apple.com/us/podcast/whatthefs/id1570521351Spotify: https://open.spotify.com/show/49d8IxKEcCOoFK4vhgyFmH?si=EFpQKn-xSzGGBiKY7HZGug&dl_branch=1@What_TheFs is my twitter handle...hope to see you there too.Enjoy What The X!!!

The title may sound like a vampire holiday movie, but most investors will be familiar with the term FAANG as an acronym for some of the most exciting tech companies in the world (Facebook, Amazon, Apple, Netflix and Google). The term BEACH is less common and is used to describe travel and leisure industries that will benefit from a return to normality after the pandemic. In Episode 24 of Magic Markets, hosts The Finance Ghost and Mohammed Nalla (Moe-Knows.com) discuss the companies behind the acronyms and what investors should be thinking about when analysing them.

Political economist Jason Smith, (@profitratedown) author of 'Smart Machines and Service Work: Automation in and Age of Stagnation', joins Sean to give us all an update on how that dang line is doing. What is the source of all of America's various morbid symptoms the last 12 to 40 years? How can it be that a handful of tech companies (the FAANGS) can seem to be so profitable when the 'real economy' is so depressed? What does all this mean for a return to social democratic, non-revolutionary politics in the capitalist core? And if you've ever wondered just why all the jobs, including perhaps your own, as so shitty these days, we ask: what is service work, really, and how does it fit into the schema of capitalist production. Finally, what is the future of work? Bonus episode on the end of Trump and the GameStop debacle out on Friday! Jason's book: https://press.uchicago.edu/ucp/books/book/distributed/S/bo70564105.html Support the Antifada by becoming a Patron!!! Closing song: Daisy Chainsaw - Love your money

The FANGS are out and telecom companies don't want to get bitten. But as giants like Facebook, Apple, Amazon, Netflix, and Google build their next generation services on 5G, how does a telecom company go from “dumb pipe” to “smart collaborator?” Stephen Rose of Bell Labs says the industry has to sharpen its teeth.    Embedding telecoms into post-pandemic healthcare: https://ftr.bz/telehealth/pod  Making 5G voice pay: https://ftr.bz/5Gvoice/pod

Brian kicks things off by reviewing his Microsoft (MSFT) backspread from last episode. Spoiler alert! It worked out pretty well! Then he follows it up with some rinse-and-repeat backspreads in Facebook (FB) and Apple (AAPL). The Options Playbook is available on OptionsPlaybook.com, or on the Amazon Kindle edition.   Do you have a question that you want answered on a future episode? Send it to Brian at TheOptionsGuy@Invest.Ally.Com, or to the Options Insider at Questions@TheOptionsInsider.com. You can also find Brian on Twitter at @BrianOverby.

TRADING BLOCK Is the trade war over? Market back in rally mode. VIX off a few handles. Have the FANGs been de-fanged? Opinion: If the FAANGs have got you down, it's time to win with the WNSSS stocks https://www.marketwatch.com/story/if-the-faangs-have-got-you-down-its-time-to-win-with-the-wnsss-stocks-2018-03-29 Tesla hit $250 yesterday - off over $100 in a few weeks. Facebook annihilation continues - hit $150.80 yesterday. ODD BLOCK More Jan 2019 50 "catastrophe" puts in Tesla Motors (TSLA) Call love in Kellogg Company (K) Mid-market love in Eldorado Resorts Inc. (ERI) STRATEGY BLOCK The Rock Lobster discusses the "VIX Zone" concept AROUND THE BLOCK It's Final Four time! Battle 1: Tasty vs. Ally Invest (TradeKing) Battle 2: Tradestation vs. Lightspeed