Podcasts about PPAP

This week's EYE ON NPI is another onsemi device - this week we're looking at the NIV3071 4-Channel eFuse Solution (https://www.digikey.com/en/product-highlight/o/on-semi/niv3071-4-channel-efuse-solution) a power distribution manager that can lets you manage a product with a lot of power domains and supplies using just a couple GPIO pins. This week's product is an upgrade from the covered-earlier NIS5420 (https://blog.adafruit.com/2021/09/09/eye-on-npi-onsemi-efuse-porfolio-eyeonnpi-digikey-onsemi-digikey-adafruit/) - with a higher 8~60V input range, and 4 independently-controlled channels. When people first meet fuses, they usually see and think of classic 'wire' fuses (https://www.digikey.com/en/products/detail/bel-fuse-inc/5ST-200-R/1009012) with ceramic or glass or thermoplastic bodies, and a thin wire inside. When too much current goes through the fuse wire, it gets hotter and hotter and eventually melts, cutting off the load from the source voltage. These kinds of fuses are super cheap, very-very-low resistance, easy to find at any hardware store, and there's lots of suppliers with various current limits. However, they're one-shot usage only and only good for over-current, can't act as switches/sequencers. You need to have a way for customers to access the fuse in order to replace it. For those reasons, a lot of engineers prefer going with 'poly fuses' - fuses that are easy to mount into a circuit that auto-reset after a time (usually minutes) so that a temporary overload doesn't make the device a brick so quickly. For example, we have a chunky 24V 5A hold / 10 A trip polyfuse (https://www.digikey.com/en/products/detail/littelfuse-inc/2016L260-24MR/6347052) on the Sparkle Motion board design (https://www.adafruit.com/product/6100), designed to protect folks who accidentally have a short in the output LED strings, and want to avoid damaging the power supply or main board. Poly-fuses are a great step-up from plain wire fuses: they're fairly inexpensive, available from lots of suppliers with various current limits, and best of all the fuse auto-resets after cooling down. However, like wire fuses, they're good for over-current, can't be reset, and have some variation depending on ambient temperature: you may trip 50% higher if its cold, or lower if its hot. Thus the next generation of fuses: eFuses (https://www.digikey.com/en/product-highlight/o/on-semi/efuse-automotive-circuit-protection)! As you could imagine, these are pure-silicon fuses, with a chunky N-FET that acts as the cut-off switch, and current limiting managed as an analog feedback loop that will cut the FET when too high. We get the resetability of a polyfuse, with additional control like sequence-able enable pins and under-voltage lockout. Note that some eFuses also can do over-voltage clamps and negative voltage protection, but the NIV3071 (https://www.digikey.com/short/3v0thr1p) doesn't contain these protections, so you may want to implement those protections separately. Especially designed for automotive power systems, which tend to be 12V/24V/36V/48V multiples, the NIV3071 (https://www.digikey.com/short/3v0thr1p) is AEC−Q100 qualified and PPAP capable (https://www.onsemi.com/pub/collateral/tnd6284-d.pdf). The use of eFuses is becoming popular as cars have become more computerized and electrified, with each 'zone' in a car (https://www.onsemi.com/solutions/automotive/zonal-architecture) - such as entertainment, communication, lighting, charging and sensors - all needing separate power management. If you don't need automotive qualifications, the functionally-compatible NIS3071 (https://www.digikey.com/short/9v2dmvhf) is a couple of cents cheaper. This family of eFuses is good for up to 60V and 2.5A per channel, but if you need more per channel you can just double or triple them up to add 2.5A per. If you want less per channel, to protect low-power devices from overheating or accidental shorts, the current limit can be reduced with an external resistor. And of course, you can turn on/off each channel with a GPIO enable pin: great for sequencing your power chain to reduce stress on the power supply from inrush current, or to allow each section to stabilize and go through self-test. For your next power supply design, the onsemi NIV3071 (https://www.digikey.com/short/3v0thr1p) and NIS3071 (https://www.digikey.com/short/9v2dmvhf) offer high-voltage, high-current control in a small package and a great price. Both are in stock right now at DigiKey for immediate shipment, so you can book today and start integration by tomorrow afternoon.

Irna Phillips created the cliff-hanger in broadcast storytelling and perfected the serial drama, first in radio, then on television. She mentored the creators of All My Children, One Life to Live, The Young and the Restless and The Bold and the Beautiful. The latter two remain on television today. Phillips also created the television vixen, an archetype first seen on soap operas that still endures. Agnes Nixon and married couple William and Lee Phillip Bell worked for Phillips in Chicago. Nixon was head writer of The Guiding Light. In 1962, she wanted to do a cancer storyline, about how uterine cancer is curable if caught in time. Doctors said women proactively asked for pPap smears after watching the character Bert Bauer struggle with her health. The Bells also ushered the sexual revolution into soaps in the 1970s, with glitz and glamor and pushing the envelope on sexuality. Soap operas created complex and groundbreaking women-centered storylines. In 1964, Another World ran an abortion storyline. In 1971, All My Children's biggest vixen, Erica Kane, was a married pregnant model who didn't want to be a mother. That abortion storyline was disruptive because the character was not seen as the “right” woman to tell an abortion story. Rape storylines on soaps have played out for decades because the form allows real-time nuance with storytelling. Nothing is ever wrapped up in one “Very Special Episode.” The uniqueness of soaps, airing five days a week, allows for pioneering storytelling.

　株式会社ラックは10月22日、「セキュリティ運用自動化支援サービス for Microsoft 365」を同日から提供開始すると発表した。

　クオリティアは、ユーザー企業やセキュリティ企業の皆がうすうす気がついてはいたが、空気を読んで誰もが口をつぐんできた、例の「ふたつの不都合な真実」を講演で言っちゃうのである。

On this episode of the podcast, I was joined by Ben Locwin, Executive SME at Black Diamond Networks. Ben and I discuss:  01:53 Material Qualification Discussion Begins 02:23 Material Qualification in Drugs vs. Devices 04:00 Quality Standards in Different Industries 08:54 Quality Tools and Their Applications 11:22 Material Qualification and Supplier Management 26:37 Regulations and Quality by Design 27:45 Closing Remarks and Guest's Current Work Ben's Article: Catalent Acquisition by Novo Holdings: Evolution of the Industry(?) Ben Locwin is a Healthcare Executive, MMA fighter, Jiu Jtisu pro and Quality and Regulatory SME working in medical devices, pharma and other regulated industries.

Dawnlough Precision is a subcontract manufacturing business that has travelled a relentless journey of growth since it started manufacturing tooling for the aerospace and medical industries back at the start of the millennium. The ascension to success has arrived through an aggressive growth strategy and investment in high-end machine tools. Part of this high-level investment journey has included the arrival of two Bumotec 191neo turn/mill centres from Starrag. By Rhys Williams Initially founded in 1987, the turn of the millennium has seen the Galway manufacturer gain accreditation to ISO: 9001, ISO: 13485 and AS: 9100D, establish a design department and increase its manufacturing facility to 50,000sq/ft. Underpinning this growth is the adoption of advanced production tools such as FMEA, PPAP and SPC. To maintain its growth trajectory, Dawnlough has invested in the most flexible, capable and productive machine tools – and this is why it has recently taken delivery of two Bumotec 191neo machines. The world-class production facility on the West Ireland coast has more than 54 CNC machine tools that provide premium manufacturing solutions. Recently acquired by the Acrotec Group, the 110-employee business is still run by longstanding Managing Director and previous owner Brian McKeon.  Looking at the path the business is taking, Keith Kennedy, Aerospace Production Manager at Dawnlough says: “We manufacture high precision components for the Aerospace and Robotic Assisted Surgical Industries as well as tooling and production aids for the medical device sector. When I started in 2006, tooling was the main business focus, but as the aerospace and medical device industries have expanded locally this presented many opportunities. Our aerospace work started with seating components for Rockwell Collins, which led us to 5-axis machining. We then progressed to flight-critical components for the likes of Spirit Aero Systems and Pratt & Whitney. Similarly, we progressed from manufacturing medical tooling and instruments to producing complete assemblies.” Discussing the expansion in the medical industry, Keith continues: “Our core business has predominantly focused on vascular work and from this, we have expanded our offering. We now produce an array of components for our RAS customers as well as consumable instruments. The First Bumotec on the Emerald Isle It is here that the search for a suitable machine led Dawnlough to purchase a Bumotec 191neo FTL-R in June 2022. Discussing the acquisition, Keith recalls: “We had several components we initially targeted for this type of machine.”  “We needed a machine with very high levels of accuracy, short cycle times and incredible efficiency because it's a very competitive market. We visited many companies, reviewing high-accuracy machines, but it's only as you look closer and purchase one of these machines for this type of work - you really see the ‘value-add' they bring. We were looking for repeatability, flexibility, high spindle speeds, the ability to machine hard material and 2-3µm precision on production runs. We had very specific requirements and we were not sure if it was going to be achievable.” “Some of our initial trial parts were 46HRc and we are using tools from 0.1 to 0.5mm. We needed repeatability of 2 to 3µm, but we needed to hold that overnight. Some of the functions of the Bumotec machine such as the software for monitoring the machine, the cutting load, the contact cutting time and the large 90 tool ATC in the machine are incredible.” “It was a huge investment and an unknown risk, but the Bumotec ticked all of our boxes. The big thing about Bumotec was the flexibility. It offered everything we wanted. It's an exceptional machine with accuracy that takes our business to a different level.”  As well as machining 46HRc parts, there was also a need for specific RAS parts that were a key driver to the first Bumotec installation, Keith says: “We were machining these parts in batches of 200-off up to six times a year and there are 6 different parts in the family with a projected ramp-up of 200-300% a year. So, we wouldn't have been able to support the customer with our existing method. There was also a fallout due to accuracy, as we couldn't 100% meet the GDT accuracy.” “We needed to put a bar diameter in the machine up to 1.5 inches whilst also running high precision production runs of small instrumentation parts. The Bumotec also had the sub-spindle and a robotic unit which was important, as we need traceability for every part we make. We took demonstration parts to Bumotec in Switzerland in April 2022 and we received the machine in June. Success Brings Machine Number 2… Following the success of the Bumotec 191neo with FTL-R configuration, the Galway company then added a second Bumotec 191neo in March 2023. Supplied with an FTL-PRM configuration, the second Bumotec 191neo was introduced with complete automation and a 20-position pallet station for lights-out production. As Keith continues: “What they offered us with the second machine was a complete turnkey solution for our instrumentation components. We had given them a target for extreme levels of precision and production volume with the flexibility to produce families of parts.” “We needed to machine materials from 46 to 52HRc such as 17-4 and 420 stainless steel as well as titanium. The instrument parts for use in invasive robotic surgery include tools like grippers, cutting instruments and scissors. We are producing the parts in medium to high volume runs across two different parts in various quantities per month.” Some of the parts had very long cycle times on the 5-axis machines and this needed to be reduced to below 30 minutes with 48HRc material. Not only was the cycle time a challenge, but Dawnlough had to attain precision levels in a production environment with the flexibility to produce upwards of 30 different components. Initially machining 20 to 50 parts a month, the schedule was set to rise rapidly to 200 parts per month before reaching production volumes – numbers not possible on a 5-axis machining centre.  “With the second machine, we knew exactly what Bumotec could offer, so we worked with them remotely. What Bumotec offer is exceptional and way beyond anything we had anticipated. With the original Bumotec 191neo FTL-R, we had the sub-spindle, but with the next set of parts we needed the Bumotec 191neo FTL-PRM. With this machine, we had the option of the vice, a 3m bar feed and also a robot loader. We needed the robot loader for traceability. It also expanded the capacity of the machine where we could go from 50mm barfed stock to 80mm billet loading.” “The sub-spindle option we had on the FTL-R wasn't feasible for the parts we needed, whereas the FTL-PRM gave us two vices. Without the vices, we would have needed to undertake secondary machining, so to be able to pick up the component in the vice and conduct the second operation in a single cycle was key to finishing the parts.” Contributing to the conversation, Dawnlough's General Manager, Mr Eddie McHugh adds: “We were machining parts on our 5-axis machining centres and we needed to increase output by 400%. We were machining around 400 parts a month on two different products with a cycle time of 45 minutes. This was tying up two machines and one man permanently every month. On second and third shifts with fewer staff, we had concerns about machine tolerance drift, so output was reduced and it also made inspection labour intensive.”  Looking at additional savings with the arrival of the Bumotec 191neo FTL-PRM, Eddie adds: “There is a labour saving with one man running two machines around the clock. Additionally, with the pallet loader, the parts are loaded into the machine and back to the pallet loader in a specific order which made huge savings on inspection. We have also made considerable savings on tool costs and changeovers and this is a credit to the 40,000rpm spindle.” With machine tools from 10 different manufacturers, Dawnlough has one machine alongside the two Bumotec 191neo that is commonly used in the medical industry. Comparing this machine to the Bumotec, Keith continues: “In comparison, the Bumotec has increased capacity, it has a larger tool library, higher spindle speeds, a larger diameter bar capacity and a lot of other features that just offers so much more flexibility. It's not only a better and more flexible option, it's a more robust machine.” The Future Looking to the future, Dawnlough has plans for more Bumotec machines and continued expansion, which will certainly continue with the ambition of the Acrotec Group. “The machines are extremely flexible and this means we can just change the programmes over, the jaws and collets and it is ready to go in less than 2 hours. For our high-precision mid to high volumes with a high mix of complexity – the Bumotec is the perfect machine for our business.” Service Dawnlough is well positioned to serve its customers – but machine tool suppliers have not always served Dawnlough with a level of customer support that a leading manufacturer would expect. Referring to the service and support from Bumotec, Keith concludes: “The service is exceptional. There is absolutely no comparison to some of our other machine suppliers. Starrag is a brand with a limited footprint in Ireland and I believe our Bumotec was their first machine in Ireland. Despite other brands having a larger footprint in the area, the Bumotec support is second to none.”  Eddie concurs by adding: “The service from Bumotec is probably the best we have had. If you need engineering support they are there straightaway, whether it's engineering support, post-processors, technical queries or anything else. The support has been fantastic.”

The good old days of the fastener industry are right now, as Jim Derry and Adam Derry of Field Fastener grow their successful family business and learn along the way (1:35:13). Industry pundit, Bob "GQ" Baer asks senior Baird analyst David Manthey to explain the inventory component of the FDI (25:22). On the Fastener News Report, Star Stainless president Tim Roberto Jr. sits in with Mike McNulty to review the encouraging numbers (50:44).  Industry educator Carmen Vertullo speaks on the PPAP process on the Fastener Training Minute (1:22:16). PLUS: Fastener Fair USA show manager Blanca Delgado previews this year's May event in Cleveland (39:37). Brian and Eric keep things predominantly fastener related, hardly mention hydrogen embrittlement at all, and agree that it's good to be part of the fastener industry. Run time: 02:18:55

Our next 2 big events are AI UX and the World's Fair. Join and apply to speak/sponsor!Due to timing issues we didn't have an interview episode to share with you this week, but not to worry, we have more than enough “weekend special” content in the backlog for you to get your Latent Space fix, whether you like thinking about the big picture, or learning more about the pod behind the scenes, or talking Groq and GPUs, or AI Leadership, or Personal AI. Enjoy!AI BreakdownThe indefatigable NLW had us back on his show for an update on the Four Wars, covering Sora, Suno, and the reshaped GPT-4 Class Landscape:and a longer segment on AI Engineering trends covering the future LLM landscape (Llama 3, GPT-5, Gemini 2, Claude 4), Open Source Models (Mistral, Grok), Apple and Meta's AI strategy, new chips (Groq, MatX) and the general movement from baby AGIs to vertical Agents:Thursday Nights in AIWe're also including swyx's interview with Josh Albrecht and Ali Rohde to reintroduce swyx and Latent Space to a general audience, and engage in some spicy Q&A:Dylan Patel on GroqWe hosted a private event with Dylan Patel of SemiAnalysis (our last pod here):Not all of it could be released so we just talked about our Groq estimates:Milind Naphade - Capital OneIn relation to conversations at NeurIPS and Nvidia GTC and upcoming at World's Fair, we also enjoyed chatting with Milind Naphade about his AI Leadership work at IBM, Cisco, Nvidia, and now leading the AI Foundations org at Capital One. We covered:* Milind's learnings from ~25 years in machine learning * His first paper citation was 24 years ago* Lessons from working with Jensen Huang for 6 years and being CTO of Metropolis * Thoughts on relevant AI research* GTC takeaways and what makes NVIDIA specialIf you'd like to work on building solutions rather than platform (as Milind put it), his Applied AI Research team at Capital One is hiring, which falls under the Capital One Tech team.Personal AI MeetupIt all started with a meme:Within days of each other, BEE, FRIEND, EmilyAI, Compass, Nox and LangFriend were all launching personal AI wearables and assistants. So we decided to put together a the world's first Personal AI meetup featuring creators and enthusiasts of wearables. The full video is live now, with full show notes within.Timestamps* [00:01:13] AI Breakdown Part 1* [00:02:20] Four Wars* [00:13:45] Sora* [00:15:12] Suno* [00:16:34] The GPT-4 Class Landscape* [00:17:03] Data War: Reddit x Google* [00:21:53] Gemini 1.5 vs Claude 3* [00:26:58] AI Breakdown Part 2* [00:27:33] Next Frontiers: Llama 3, GPT-5, Gemini 2, Claude 4* [00:31:11] Open Source Models - Mistral, Grok* [00:34:13] Apple MM1* [00:37:33] Meta's $800b AI rebrand* [00:39:20] AI Engineer landscape - from baby AGIs to vertical Agents* [00:47:28] Adept episode - Screen Multimodality* [00:48:54] Top Model Research from January Recap* [00:53:08] AI Wearables* [00:57:26] Groq vs Nvidia month - GPU Chip War* [01:00:31] Disagreements* [01:02:08] Summer 2024 Predictions* [01:04:18] Thursday Nights in AI - swyx* [01:33:34] Dylan Patel - Semianalysis + Latent Space Live Show* [01:34:58] GroqTranscript[00:00:00] swyx: Welcome to the Latent Space Podcast Weekend Edition. This is Charlie, your AI co host. Swyx and Alessio are off for the week, making more great content. We have exciting interviews coming up with Elicit, Chroma, Instructor, and our upcoming series on NSFW, Not Safe for Work AI. In today's episode, we're collating some of Swyx and Alessio's recent appearances, all in one place for you to find.[00:00:32] swyx: In part one, we have our first crossover pod of the year. In our listener survey, several folks asked for more thoughts from our two hosts. In 2023, Swyx and Alessio did crossover interviews with other great podcasts like the AI Breakdown, Practical AI, Cognitive Revolution, Thursday Eye, and Chinatalk, all of which you can find in the Latentspace About page.[00:00:56] swyx: NLW of the AI Breakdown asked us back to do a special on the 4Wars framework and the AI engineer scene. We love AI Breakdown as one of the best examples Daily podcasts to keep up on AI news, so we were especially excited to be back on Watch out and take[00:01:12] NLW: care[00:01:13] AI Breakdown Part 1[00:01:13] NLW: today on the AI breakdown. Part one of my conversation with Alessio and Swix from Latent Space.[00:01:19] NLW: All right, fellas, welcome back to the AI Breakdown. How are you doing? I'm good. Very good. With the last, the last time we did this show, we were like, oh yeah, let's do check ins like monthly about all the things that are going on and then. Of course, six months later, and, you know, the, the, the world has changed in a thousand ways.[00:01:36] NLW: It's just, it's too busy to even, to even think about podcasting sometimes. But I, I'm super excited to, to be chatting with you again. I think there's, there's a lot to, to catch up on, just to tap in, I think in the, you know, in the beginning of 2024. And, and so, you know, we're gonna talk today about just kind of a, a, a broad sense of where things are in some of the key battles in the AI space.[00:01:55] NLW: And then the, you know, one of the big things that I, that I'm really excited to have you guys on here for us to talk about where, sort of what patterns you're seeing and what people are actually trying to build, you know, where, where developers are spending their, their time and energy and, and, and any sort of, you know, trend trends there, but maybe let's start I guess by checking in on a framework that you guys actually introduced, which I've loved and I've cribbed a couple of times now, which is this sort of four wars of the, of the AI stack.[00:02:20] Four Wars[00:02:20] NLW: Because first, since I have you here, I'd love, I'd love to hear sort of like where that started gelling. And then and then maybe we can get into, I think a couple of them that are you know, particularly interesting, you know, in the, in light of[00:02:30] swyx: some recent news. Yeah, so maybe I'll take this one. So the four wars is a framework that I came up around trying to recap all of 2023.[00:02:38] swyx: I tried to write sort of monthly recap pieces. And I was trying to figure out like what makes one piece of news last longer than another or more significant than another. And I think it's basically always around battlegrounds. Wars are fought around limited resources. And I think probably the, you know, the most limited resource is talent, but the talent expresses itself in a number of areas.[00:03:01] swyx: And so I kind of focus on those, those areas at first. So the four wars that we cover are the data wars, the GPU rich, poor war, the multi modal war, And the RAG and Ops War. And I think you actually did a dedicated episode to that, so thanks for covering that. Yeah, yeah.[00:03:18] NLW: Not only did I do a dedicated episode, I actually used that.[00:03:22] NLW: I can't remember if I told you guys. I did give you big shoutouts. But I used it as a framework for a presentation at Intel's big AI event that they hold each year, where they have all their folks who are working on AI internally. And it totally resonated. That's amazing. Yeah, so, so, what got me thinking about it again is specifically this inflection news that we recently had, this sort of, you know, basically, I can't imagine that anyone who's listening wouldn't have thought about it, but, you know, inflection is a one of the big contenders, right?[00:03:53] NLW: I think probably most folks would have put them, you know, just a half step behind the anthropics and open AIs of the world in terms of labs, but it's a company that raised 1. 3 billion last year, less than a year ago. Reed Hoffman's a co founder Mustafa Suleyman, who's a co founder of DeepMind, you know, so it's like, this is not a a small startup, let's say, at least in terms of perception.[00:04:13] NLW: And then we get the news that basically most of the team, it appears, is heading over to Microsoft and they're bringing in a new CEO. And you know, I'm interested in, in, in kind of your take on how much that reflects, like hold aside, I guess, you know, all the other things that it might be about, how much it reflects this sort of the, the stark.[00:04:32] NLW: Brutal reality of competing in the frontier model space right now. And, you know, just the access to compute.[00:04:38] Alessio: There are a lot of things to say. So first of all, there's always somebody who's more GPU rich than you. So inflection is GPU rich by startup standard. I think about 22, 000 H100s, but obviously that pales compared to the, to Microsoft.[00:04:55] Alessio: The other thing is that this is probably good news, maybe for the startups. It's like being GPU rich, it's not enough. You know, like I think they were building something pretty interesting in, in pi of their own model of their own kind of experience. But at the end of the day, you're the interface that people consume as end users.[00:05:13] Alessio: It's really similar to a lot of the others. So and we'll tell, talk about GPT four and cloud tree and all this stuff. GPU poor, doing something. That the GPU rich are not interested in, you know we just had our AI center of excellence at Decibel and one of the AI leads at one of the big companies was like, Oh, we just saved 10 million and we use these models to do a translation, you know, and that's it.[00:05:39] Alessio: It's not, it's not a GI, it's just translation. So I think like the inflection part is maybe. A calling and a waking to a lot of startups then say, Hey, you know, trying to get as much capital as possible, try and get as many GPUs as possible. Good. But at the end of the day, it doesn't build a business, you know, and maybe what inflection I don't, I don't, again, I don't know the reasons behind the inflection choice, but if you say, I don't want to build my own company that has 1.[00:06:05] Alessio: 3 billion and I want to go do it at Microsoft, it's probably not a resources problem. It's more of strategic decisions that you're making as a company. So yeah, that was kind of my. I take on it.[00:06:15] swyx: Yeah, and I guess on my end, two things actually happened yesterday. It was a little bit quieter news, but Stability AI had some pretty major departures as well.[00:06:25] swyx: And you may not be considering it, but Stability is actually also a GPU rich company in the sense that they were the first new startup in this AI wave to brag about how many GPUs that they have. And you should join them. And you know, Imadis is definitely a GPU trader in some sense from his hedge fund days.[00:06:43] swyx: So Robin Rhombach and like the most of the Stable Diffusion 3 people left Stability yesterday as well. So yesterday was kind of like a big news day for the GPU rich companies, both Inflection and Stability having sort of wind taken out of their sails. I think, yes, it's a data point in the favor of Like, just because you have the GPUs doesn't mean you can, you automatically win.[00:07:03] swyx: And I think, you know, kind of I'll echo what Alessio says there. But in general also, like, I wonder if this is like the start of a major consolidation wave, just in terms of, you know, I think that there was a lot of funding last year and, you know, the business models have not been, you know, All of these things worked out very well.[00:07:19] swyx: Even inflection couldn't do it. And so I think maybe that's the start of a small consolidation wave. I don't think that's like a sign of AI winter. I keep looking for AI winter coming. I think this is kind of like a brief cold front. Yeah,[00:07:34] NLW: it's super interesting. So I think a bunch of A bunch of stuff here.[00:07:38] NLW: One is, I think, to both of your points, there, in some ways, there, there had already been this very clear demarcation between these two sides where, like, the GPU pores, to use the terminology, like, just weren't trying to compete on the same level, right? You know, the vast majority of people who have started something over the last year, year and a half, call it, were racing in a different direction.[00:07:59] NLW: They're trying to find some edge somewhere else. They're trying to build something different. If they're, if they're really trying to innovate, it's in different areas. And so it's really just this very small handful of companies that are in this like very, you know, it's like the coheres and jaspers of the world that like this sort of, you know, that are that are just sort of a little bit less resourced than, you know, than the other set that I think that this potentially even applies to, you know, everyone else that could clearly demarcate it into these two, two sides.[00:08:26] NLW: And there's only a small handful kind of sitting uncomfortably in the middle, perhaps. Let's, let's come back to the idea of, of the sort of AI winter or, you know, a cold front or anything like that. So this is something that I, I spent a lot of time kind of thinking about and noticing. And my perception is that The vast majority of the folks who are trying to call for sort of, you know, a trough of disillusionment or, you know, a shifting of the phase to that are people who either, A, just don't like AI for some other reason there's plenty of that, you know, people who are saying, You Look, they're doing way worse than they ever thought.[00:09:03] NLW: You know, there's a lot of sort of confirmation bias kind of thing going on. Or two, media that just needs a different narrative, right? Because they're sort of sick of, you know, telling the same story. Same thing happened last summer, when every every outlet jumped on the chat GPT at its first down month story to try to really like kind of hammer this idea that that the hype was too much.[00:09:24] NLW: Meanwhile, you have, you know, just ridiculous levels of investment from enterprises, you know, coming in. You have, you know, huge, huge volumes of, you know, individual behavior change happening. But I do think that there's nothing incoherent sort of to your point, Swyx, about that and the consolidation period.[00:09:42] NLW: Like, you know, if you look right now, for example, there are, I don't know, probably 25 or 30 credible, like, build your own chatbot. platforms that, you know, a lot of which have, you know, raised funding. There's no universe in which all of those are successful across, you know, even with a, even, even with a total addressable market of every enterprise in the world, you know, you're just inevitably going to see some amount of consolidation.[00:10:08] NLW: Same with, you know, image generators. There are, if you look at A16Z's top 50 consumer AI apps, just based on, you know, web traffic or whatever, they're still like I don't know, a half. Dozen or 10 or something, like, some ridiculous number of like, basically things like Midjourney or Dolly three. And it just seems impossible that we're gonna have that many, you know, ultimately as, as, as sort of, you know, going, going concerned.[00:10:33] NLW: So, I don't know. I, I, I think that the, there will be inevitable consolidation 'cause you know. It's, it's also what kind of like venture rounds are supposed to do. You're not, not everyone who gets a seed round is supposed to get to series A and not everyone who gets a series A is supposed to get to series B.[00:10:46] NLW: That's sort of the natural process. I think it will be tempting for a lot of people to try to infer from that something about AI not being as sort of big or as as sort of relevant as, as it was hyped up to be. But I, I kind of think that's the wrong conclusion to come to.[00:11:02] Alessio: I I would say the experimentation.[00:11:04] Alessio: Surface is a little smaller for image generation. So if you go back maybe six, nine months, most people will tell you, why would you build a coding assistant when like Copilot and GitHub are just going to win everything because they have the data and they have all the stuff. If you fast forward today, A lot of people use Cursor everybody was excited about the Devin release on Twitter.[00:11:26] Alessio: There are a lot of different ways of attacking the market that are not completion of code in the IDE. And even Cursors, like they evolved beyond single line to like chat, to do multi line edits and, and all that stuff. Image generation, I would say, yeah, as a, just as from what I've seen, like maybe the product innovation has slowed down at the UX level and people are improving the models.[00:11:50] Alessio: So the race is like, how do I make better images? It's not like, how do I make the user interact with the generation process better? And that gets tough, you know? It's hard to like really differentiate yourselves. So yeah, that's kind of how I look at it. And when we think about multimodality, maybe the reason why people got so excited about Sora is like, oh, this is like a completely It's not a better image model.[00:12:13] Alessio: This is like a completely different thing, you know? And I think the creative mind It's always looking for something that impacts the viewer in a different way, you know, like they really want something different versus the developer mind. It's like, Oh, I, I just, I have this like very annoying thing I want better.[00:12:32] Alessio: I have this like very specific use cases that I want to go after. So it's just different. And that's why you see a lot more companies in image generation. But I agree with you that. If you fast forward there, there's not going to be 10 of them, you know, it's probably going to be one or[00:12:46] swyx: two. Yeah, I mean, to me, that's why I call it a war.[00:12:49] swyx: Like, individually, all these companies can make a story that kind of makes sense, but collectively, they cannot all be true. Therefore, they all, there is some kind of fight over limited resources here. Yeah, so[00:12:59] NLW: it's interesting. We wandered very naturally into sort of another one of these wars, which is the multimodality kind of idea, which is, you know, basically a question of whether it's going to be these sort of big everything models that end up winning or whether, you know, you're going to have really specific things, you know, like something, you know, Dolly 3 inside of sort of OpenAI's larger models versus, you know, a mid journey or something like that.[00:13:24] NLW: And at first, you know, I was kind of thinking like, For most of the last, call it six months or whatever, it feels pretty definitively both and in some ways, you know, and that you're, you're seeing just like great innovation on sort of the everything models, but you're also seeing lots and lots happen at sort of the level of kind of individual use cases.[00:13:45] Sora[00:13:45] NLW: But then Sora comes along and just like obliterates what I think anyone thought you know, where we were when it comes to video generation. So how are you guys thinking about this particular battle or war at the moment?[00:13:59] swyx: Yeah, this was definitely a both and story, and Sora tipped things one way for me, in terms of scale being all you need.[00:14:08] swyx: And the benefit, I think, of having multiple models being developed under one roof. I think a lot of people aren't aware that Sora was developed in a similar fashion to Dolly 3. And Dolly3 had a very interesting paper out where they talked about how they sort of bootstrapped their synthetic data based on GPT 4 vision and GPT 4.[00:14:31] swyx: And, and it was just all, like, really interesting, like, if you work on one modality, it enables you to work on other modalities, and all that is more, is, is more interesting. I think it's beneficial if it's all in the same house, whereas the individual startups who don't, who sort of carve out a single modality and work on that, definitely won't have the state of the art stuff on helping them out on synthetic data.[00:14:52] swyx: So I do think like, The balance is tilted a little bit towards the God model companies, which is challenging for the, for the, for the the sort of dedicated modality companies. But everyone's carving out different niches. You know, like we just interviewed Suno ai, the sort of music model company, and, you know, I don't see opening AI pursuing music anytime soon.[00:15:12] Suno[00:15:12] swyx: Yeah,[00:15:13] NLW: Suno's been phenomenal to play with. Suno has done that rare thing where, which I think a number of different AI product categories have done, where people who don't consider themselves particularly interested in doing the thing that the AI enables find themselves doing a lot more of that thing, right?[00:15:29] NLW: Like, it'd be one thing if Just musicians were excited about Suno and using it but what you're seeing is tons of people who just like music all of a sudden like playing around with it and finding themselves kind of down that rabbit hole, which I think is kind of like the highest compliment that you can give one of these startups at the[00:15:45] swyx: early days of it.[00:15:46] swyx: Yeah, I, you know, I, I asked them directly, you know, in the interview about whether they consider themselves mid journey for music. And he had a more sort of nuanced response there, but I think that probably the business model is going to be very similar because he's focused on the B2C element of that. So yeah, I mean, you know, just to, just to tie back to the question about, you know, You know, large multi modality companies versus small dedicated modality companies.[00:16:10] swyx: Yeah, highly recommend people to read the Sora blog posts and then read through to the Dali blog posts because they, they strongly correlated themselves with the same synthetic data bootstrapping methods as Dali. And I think once you make those connections, you're like, oh, like it, it, it is beneficial to have multiple state of the art models in house that all help each other.[00:16:28] swyx: And these, this, that's the one thing that a dedicated modality company cannot do.[00:16:34] The GPT-4 Class Landscape[00:16:34] NLW: So I, I wanna jump, I wanna kind of build off that and, and move into the sort of like updated GPT-4 class landscape. 'cause that's obviously been another big change over the last couple months. But for the sake of completeness, is there anything that's worth touching on with with sort of the quality?[00:16:46] NLW: Quality data or sort of a rag ops wars just in terms of, you know, anything that's changed, I guess, for you fundamentally in the last couple of months about where those things stand.[00:16:55] swyx: So I think we're going to talk about rag for the Gemini and Clouds discussion later. And so maybe briefly discuss the data piece.[00:17:03] Data War: Reddit x Google[00:17:03] swyx: I think maybe the only new thing was this Reddit deal with Google for like a 60 million dollar deal just ahead of their IPO, very conveniently turning Reddit into a AI data company. Also, very, very interestingly, a non exclusive deal, meaning that Reddit can resell that data to someone else. And it probably does become table stakes.[00:17:23] swyx: A lot of people don't know, but a lot of the web text dataset that originally started for GPT 1, 2, and 3 was actually scraped from GitHub. from Reddit at least the sort of vote scores. And I think, I think that's a, that's a very valuable piece of information. So like, yeah, I think people are figuring out how to pay for data.[00:17:40] swyx: People are suing each other over data. This, this, this war is, you know, definitely very, very much heating up. And I don't think, I don't see it getting any less intense. I, you know, next to GPUs, data is going to be the most expensive thing in, in a model stack company. And. You know, a lot of people are resorting to synthetic versions of it, which may or may not be kosher based on how far along or how commercially blessed the, the forms of creating that synthetic data are.[00:18:11] swyx: I don't know if Alessio, you have any other interactions with like Data source companies, but that's my two cents.[00:18:17] Alessio: Yeah yeah, I actually saw Quentin Anthony from Luther. ai at GTC this week. He's also been working on this. I saw Technium. He's also been working on the data side. I think especially in open source, people are like, okay, if everybody is putting the gates up, so to speak, to the data we need to make it easier for people that don't have 50 million a year to get access to good data sets.[00:18:38] Alessio: And Jensen, at his keynote, he did talk about synthetic data a little bit. So I think that's something that we'll definitely hear more and more of in the enterprise, which never bodes well, because then all the, all the people with the data are like, Oh, the enterprises want to pay now? Let me, let me put a pay here stripe link so that they can give me 50 million.[00:18:57] Alessio: But it worked for Reddit. I think the stock is up. 40 percent today after opening. So yeah, I don't know if it's all about the Google deal, but it's obviously Reddit has been one of those companies where, hey, you got all this like great community, but like, how are you going to make money? And like, they try to sell the avatars.[00:19:15] Alessio: I don't know if that it's a great business for them. The, the data part sounds as an investor, you know, the data part sounds a lot more interesting than, than consumer[00:19:25] swyx: cosmetics. Yeah, so I think, you know there's more questions around data you know, I think a lot of people are talking about the interview that Mira Murady did with the Wall Street Journal, where she, like, just basically had no, had no good answer for where they got the data for Sora.[00:19:39] swyx: I, I think this is where, you know, there's, it's in nobody's interest to be transparent about data, and it's, it's kind of sad for the state of ML and the state of AI research but it is what it is. We, we have to figure this out as a society, just like we did for music and music sharing. You know, in, in sort of the Napster to Spotify transition, and that might take us a decade.[00:19:59] swyx: Yeah, I[00:20:00] NLW: do. I, I agree. I think, I think that you're right to identify it, not just as that sort of technical problem, but as one where society has to have a debate with itself. Because I think that there's, if you rationally within it, there's Great kind of points on all side, not to be the sort of, you know, person who sits in the middle constantly, but it's why I think a lot of these legal decisions are going to be really important because, you know, the job of judges is to listen to all this stuff and try to come to things and then have other judges disagree.[00:20:24] NLW: And, you know, and have the rest of us all debate at the same time. By the way, as a total aside, I feel like the synthetic data right now is like eggs in the 80s and 90s. Like, whether they're good for you or bad for you, like, you know, we, we get one study that's like synthetic data, you know, there's model collapse.[00:20:42] NLW: And then we have like a hint that llama, you know, to the most high performance version of it, which was one they didn't release was trained on synthetic data. So maybe it's good. It's like, I just feel like every, every other week I'm seeing something sort of different about whether it's a good or bad for, for these models.[00:20:56] swyx: Yeah. The branding of this is pretty poor. I would kind of tell people to think about it like cholesterol. There's good cholesterol, bad cholesterol. And you can have, you know, good amounts of both. But at this point, it is absolutely without a doubt that most large models from here on out will all be trained as some kind of synthetic data and that is not a bad thing.[00:21:16] swyx: There are ways in which you can do it poorly. Whether it's commercial, you know, in terms of commercial sourcing or in terms of the model performance. But it's without a doubt that good synthetic data is going to help your model. And this is just a question of like where to obtain it and what kinds of synthetic data are valuable.[00:21:36] swyx: You know, if even like alpha geometry, you know, was, was a really good example from like earlier this year.[00:21:42] NLW: If you're using the cholesterol analogy, then my, then my egg thing can't be that far off. Let's talk about the sort of the state of the art and the, and the GPT 4 class landscape and how that's changed.[00:21:53] Gemini 1.5 vs Claude 3[00:21:53] NLW: Cause obviously, you know, sort of the, the two big things or a couple of the big things that have happened. Since we last talked, we're one, you know, Gemini first announcing that a model was coming and then finally it arriving, and then very soon after a sort of a different model arriving from Gemini and and Cloud three.[00:22:11] NLW: So I guess, you know, I'm not sure exactly where the right place to start with this conversation is, but, you know, maybe very broadly speaking which of these do you think have made a bigger impact? Thank you.[00:22:20] Alessio: Probably the one you can use, right? So, Cloud. Well, I'm sure Gemini is going to be great once they let me in, but so far I haven't been able to.[00:22:29] Alessio: I use, so I have this small podcaster thing that I built for our podcast, which does chapters creation, like named entity recognition, summarization, and all of that. Cloud Tree is, Better than GPT 4. Cloud2 was unusable. So I use GPT 4 for everything. And then when Opus came out, I tried them again side by side and I posted it on, on Twitter as well.[00:22:53] Alessio: Cloud is better. It's very good, you know, it's much better, it seems to me, it's much better than GPT 4 at doing writing that is more, you know, I don't know, it just got good vibes, you know, like the GPT 4 text, you can tell it's like GPT 4, you know, it's like, it always uses certain types of words and phrases and, you know, maybe it's just me because I've now done it for, you know, So, I've read like 75, 80 generations of these things next to each other.[00:23:21] Alessio: Clutter is really good. I know everybody is freaking out on twitter about it, my only experience of this is much better has been on the podcast use case. But I know that, you know, Quran from from News Research is a very big opus pro, pro opus person. So, I think that's also It's great to have people that actually care about other models.[00:23:40] Alessio: You know, I think so far to a lot of people, maybe Entropic has been the sibling in the corner, you know, it's like Cloud releases a new model and then OpenAI releases Sora and like, you know, there are like all these different things, but yeah, the new models are good. It's interesting.[00:23:55] NLW: My my perception is definitely that just, just observationally, Cloud 3 is certainly the first thing that I've seen where lots of people.[00:24:06] NLW: They're, no one's debating evals or anything like that. They're talking about the specific use cases that they have, that they used to use chat GPT for every day, you know, day in, day out, that they've now just switched over. And that has, I think, shifted a lot of the sort of like vibe and sentiment in the space too.[00:24:26] NLW: And I don't necessarily think that it's sort of a A like full you know, sort of full knock. Let's put it this way. I think it's less bad for open AI than it is good for anthropic. I think that because GPT 5 isn't there, people are not quite willing to sort of like, you know get overly critical of, of open AI, except in so far as they're wondering where GPT 5 is.[00:24:46] NLW: But I do think that it makes, Anthropic look way more credible as a, as a, as a player, as a, you know, as a credible sort of player, you know, as opposed to to, to where they were.[00:24:57] Alessio: Yeah. And I would say the benchmarks veil is probably getting lifted this year. I think last year. People were like, okay, this is better than this on this benchmark, blah, blah, blah, because maybe they did not have a lot of use cases that they did frequently.[00:25:11] Alessio: So it's hard to like compare yourself. So you, you defer to the benchmarks. I think now as we go into 2024, a lot of people have started to use these models from, you know, from very sophisticated things that they run in production to some utility that they have on their own. Now they can just run them side by side.[00:25:29] Alessio: And it's like, Hey, I don't care that like. The MMLU score of Opus is like slightly lower than GPT 4. It just works for me, you know, and I think that's the same way that traditional software has been used by people, right? Like you just strive for yourself and like, which one does it work, works best for you?[00:25:48] Alessio: Like nobody looks at benchmarks outside of like sales white papers, you know? And I think it's great that we're going more in that direction. We have a episode with Adapt coming out this weekend. I'll and some of their model releases, they specifically say, We do not care about benchmarks, so we didn't put them in, you know, because we, we don't want to look good on them.[00:26:06] Alessio: We just want the product to work. And I think more and more people will, will[00:26:09] swyx: go that way. Yeah. I I would say like, it does take the wind out of the sails for GPT 5, which I know where, you know, Curious about later on. I think anytime you put out a new state of the art model, you have to break through in some way.[00:26:21] swyx: And what Claude and Gemini have done is effectively take away any advantage to saying that you have a million token context window. Now everyone's just going to be like, Oh, okay. Now you just match the other two guys. And so that puts An insane amount of pressure on what gpt5 is going to be because it's just going to have like the only option it has now because all the other models are multimodal all the other models are long context all the other models have perfect recall gpt5 has to match everything and do more to to not be a flop[00:26:58] AI Breakdown Part 2[00:26:58] NLW: hello friends back again with part two if you haven't heard part one of this conversation i suggest you go check it out but to be honest they are kind of actually separable In this conversation, we get into a topic that I think Alessio and Swyx are very well positioned to discuss, which is what developers care about right now, what people are trying to build around.[00:27:16] NLW: I honestly think that one of the best ways to see the future in an industry like AI is to try to dig deep on what developers and entrepreneurs are attracted to build, even if it hasn't made it to the news pages yet. So consider this your preview of six months from now, and let's dive in. Let's bring it to the GPT 5 conversation.[00:27:33] Next Frontiers: Llama 3, GPT-5, Gemini 2, Claude 4[00:27:33] NLW: I mean, so, so I think that that's a great sort of assessment of just how the stakes have been raised, you know is your, I mean, so I guess maybe, maybe I'll, I'll frame this less as a question, just sort of something that, that I, that I've been watching right now, the only thing that makes sense to me with how.[00:27:50] NLW: Fundamentally unbothered and unstressed OpenAI seems about everything is that they're sitting on something that does meet all that criteria, right? Because, I mean, even in the Lex Friedman interview that, that Altman recently did, you know, he's talking about other things coming out first. He's talking about, he's just like, he, listen, he, he's good and he could play nonchalant, you know, if he wanted to.[00:28:13] NLW: So I don't want to read too much into it, but. You know, they've had so long to work on this, like unless that we are like really meaningfully running up against some constraint, it just feels like, you know, there's going to be some massive increase, but I don't know. What do you guys think?[00:28:28] swyx: Hard to speculate.[00:28:29] swyx: You know, at this point, they're, they're pretty good at PR and they're not going to tell you anything that they don't want to. And he can tell you one thing and change their minds the next day. So it's, it's, it's really, you know, I've always said that model version numbers are just marketing exercises, like they have something and it's always improving and at some point you just cut it and decide to call it GPT 5.[00:28:50] swyx: And it's more just about defining an arbitrary level at which they're ready and it's up to them on what ready means. We definitely did see some leaks on GPT 4. 5, as I think a lot of people reported and I'm not sure if you covered it. So it seems like there might be an intermediate release. But I did feel, coming out of the Lex Friedman interview, that GPT 5 was nowhere near.[00:29:11] swyx: And you know, it was kind of a sharp contrast to Sam talking at Davos in February, saying that, you know, it was his top priority. So I find it hard to square. And honestly, like, there's also no point Reading too much tea leaves into what any one person says about something that hasn't happened yet or has a decision that hasn't been taken yet.[00:29:31] swyx: Yeah, that's, that's my 2 cents about it. Like, calm down, let's just build .[00:29:35] Alessio: Yeah. The, the February rumor was that they were gonna work on AI agents, so I don't know, maybe they're like, yeah,[00:29:41] swyx: they had two agent two, I think two agent projects, right? One desktop agent and one sort of more general yeah, sort of GPTs like agent and then Andre left, so he was supposed to be the guy on that.[00:29:52] swyx: What did Andre see? What did he see? I don't know. What did he see?[00:29:56] Alessio: I don't know. But again, it's just like the rumors are always floating around, you know but I think like, this is, you know, we're not going to get to the end of the year without Jupyter you know, that's definitely happening. I think the biggest question is like, are Anthropic and Google.[00:30:13] Alessio: Increasing the pace, you know, like it's the, it's the cloud four coming out like in 12 months, like nine months. What's the, what's the deal? Same with Gemini. They went from like one to 1. 5 in like five days or something. So when's Gemini 2 coming out, you know, is that going to be soon? I don't know.[00:30:31] Alessio: There, there are a lot of, speculations, but the good thing is that now you can see a world in which OpenAI doesn't rule everything. You know, so that, that's the best, that's the best news that everybody got, I would say.[00:30:43] swyx: Yeah, and Mistral Large also dropped in the last month. And, you know, not as, not quite GPT 4 class, but very good from a new startup.[00:30:52] swyx: So yeah, we, we have now slowly changed in landscape, you know. In my January recap, I was complaining that nothing's changed in the landscape for a long time. But now we do exist in a world, sort of a multipolar world where Cloud and Gemini are legitimate challengers to GPT 4 and hopefully more will emerge as well hopefully from meta.[00:31:11] Open Source Models - Mistral, Grok[00:31:11] NLW: So speak, let's actually talk about sort of the open source side of this for a minute. So Mistral Large, notable because it's, it's not available open source in the same way that other things are, although I think my perception is that the community has largely given them Like the community largely recognizes that they want them to keep building open source stuff and they have to find some way to fund themselves that they're going to do that.[00:31:27] NLW: And so they kind of understand that there's like, they got to figure out how to eat, but we've got, so, you know, there there's Mistral, there's, I guess, Grok now, which is, you know, Grok one is from, from October is, is open[00:31:38] swyx: sourced at, yeah. Yeah, sorry, I thought you thought you meant Grok the chip company.[00:31:41] swyx: No, no, no, yeah, you mean Twitter Grok.[00:31:43] NLW: Although Grok the chip company, I think is even more interesting in some ways, but and then there's the, you know, obviously Llama3 is the one that sort of everyone's wondering about too. And, you know, my, my sense of that, the little bit that, you know, Zuckerberg was talking about Llama 3 earlier this year, suggested that, at least from an ambition standpoint, he was not thinking about how do I make sure that, you know, meta content, you know, keeps, keeps the open source thrown, you know, vis a vis Mistral.[00:32:09] NLW: He was thinking about how you go after, you know, how, how he, you know, releases a thing that's, you know, every bit as good as whatever OpenAI is on at that point.[00:32:16] Alessio: Yeah. From what I heard in the hallways at, at GDC, Llama 3, the, the biggest model will be, you 260 to 300 billion parameters, so that that's quite large.[00:32:26] Alessio: That's not an open source model. You know, you cannot give people a 300 billion parameters model and ask them to run it. You know, it's very compute intensive. So I think it is, it[00:32:35] swyx: can be open source. It's just, it's going to be difficult to run, but that's a separate question.[00:32:39] Alessio: It's more like, as you think about what they're doing it for, you know, it's not like empowering the person running.[00:32:45] Alessio: llama. On, on their laptop, it's like, oh, you can actually now use this to go after open AI, to go after Anthropic, to go after some of these companies at like the middle complexity level, so to speak. Yeah. So obviously, you know, we estimate Gentala on the podcast, they're doing a lot here, they're making PyTorch better.[00:33:03] Alessio: You know, they want to, that's kind of like maybe a little bit of a shorted. Adam Bedia, in a way, trying to get some of the CUDA dominance out of it. Yeah, no, it's great. The, I love the duck destroying a lot of monopolies arc. You know, it's, it's been very entertaining. Let's bridge[00:33:18] NLW: into the sort of big tech side of this, because this is obviously like, so I think actually when I did my episode, this was one of the I added this as one of as an additional war that, that's something that I'm paying attention to.[00:33:29] NLW: So we've got Microsoft's moves with inflection, which I think pretend, potentially are being read as A shift vis a vis the relationship with OpenAI, which also the sort of Mistral large relationship seems to reinforce as well. We have Apple potentially entering the race, finally, you know, giving up Project Titan and and, and kind of trying to spend more effort on this.[00:33:50] NLW: Although, Counterpoint, we also have them talking about it, or there being reports of a deal with Google, which, you know, is interesting to sort of see what their strategy there is. And then, you know, Meta's been largely quiet. We kind of just talked about the main piece, but, you know, there's, and then there's spoilers like Elon.[00:34:07] NLW: I mean, you know, what, what of those things has sort of been most interesting to you guys as you think about what's going to shake out for the rest of this[00:34:13] Apple MM1[00:34:13] swyx: year? I'll take a crack. So the reason we don't have a fifth war for the Big Tech Wars is that's one of those things where I just feel like we don't cover differently from other media channels, I guess.[00:34:26] swyx: Sure, yeah. In our anti interestness, we actually say, like, we try not to cover the Big Tech Game of Thrones, or it's proxied through Twitter. You know, all the other four wars anyway, so there's just a lot of overlap. Yeah, I think absolutely, personally, the most interesting one is Apple entering the race.[00:34:41] swyx: They actually released, they announced their first large language model that they trained themselves. It's like a 30 billion multimodal model. People weren't that impressed, but it was like the first time that Apple has kind of showcased that, yeah, we're training large models in house as well. Of course, like, they might be doing this deal with Google.[00:34:57] swyx: I don't know. It sounds very sort of rumor y to me. And it's probably, if it's on device, it's going to be a smaller model. So something like a Jemma. It's going to be smarter autocomplete. I don't know what to say. I'm still here dealing with, like, Siri, which hasn't, probably hasn't been updated since God knows when it was introduced.[00:35:16] swyx: It's horrible. I, you know, it, it, it makes me so angry. So I, I, one, as an Apple customer and user, I, I'm just hoping for better AI on Apple itself. But two, they are the gold standard when it comes to local devices, personal compute and, and trust, like you, you trust them with your data. And. I think that's what a lot of people are looking for in AI, that they have, they love the benefits of AI, they don't love the downsides, which is that you have to send all your data to some cloud somewhere.[00:35:45] swyx: And some of this data that we're going to feed AI is just the most personal data there is. So Apple being like one of the most trusted personal data companies, I think it's very important that they enter the AI race, and I hope to see more out of them.[00:35:58] Alessio: To me, the, the biggest question with the Google deal is like, who's paying who?[00:36:03] Alessio: Because for the browsers, Google pays Apple like 18, 20 billion every year to be the default browser. Is Google going to pay you to have Gemini or is Apple paying Google to have Gemini? I think that's, that's like what I'm most interested to figure out because with the browsers, it's like, it's the entry point to the thing.[00:36:21] Alessio: So it's really valuable to be the default. That's why Google pays. But I wonder if like the perception in AI is going to be like, Hey. You just have to have a good local model on my phone to be worth me purchasing your device. And that was, that's kind of drive Apple to be the one buying the model. But then, like Shawn said, they're doing the MM1 themselves.[00:36:40] Alessio: So are they saying we do models, but they're not as good as the Google ones? I don't know. The whole thing is, it's really confusing, but. It makes for great meme material on on Twitter.[00:36:51] swyx: Yeah, I mean, I think, like, they are possibly more than OpenAI and Microsoft and Amazon. They are the most full stack company there is in computing, and so, like, they own the chips, man.[00:37:05] swyx: Like, they manufacture everything so if, if, if there was a company that could do that. You know, seriously challenge the other AI players. It would be Apple. And it's, I don't think it's as hard as self driving. So like maybe they've, they've just been investing in the wrong thing this whole time. We'll see.[00:37:21] swyx: Wall Street certainly thinks[00:37:22] NLW: so. Wall Street loved that move, man. There's a big, a big sigh of relief. Well, let's, let's move away from, from sort of the big stuff. I mean, the, I think to both of your points, it's going to.[00:37:33] Meta's $800b AI rebrand[00:37:33] NLW: Can I, can[00:37:34] swyx: I, can I, can I jump on factoid about this, this Wall Street thing? I went and looked at when Meta went from being a VR company to an AI company.[00:37:44] swyx: And I think the stock I'm trying to look up the details now. The stock has gone up 187% since Lamo one. Yeah. Which is $830 billion in market value created in the past year. . Yeah. Yeah.[00:37:57] NLW: It's, it's, it's like, remember if you guys haven't Yeah. If you haven't seen the chart, it's actually like remarkable.[00:38:02] NLW: If you draw a little[00:38:03] swyx: arrow on it, it's like, no, we're an AI company now and forget the VR thing.[00:38:10] NLW: It's it, it is an interesting, no, it's, I, I think, alessio, you called it sort of like Zuck's Disruptor Arc or whatever. He, he really does. He is in the midst of a, of a total, you know, I don't know if it's a redemption arc or it's just, it's something different where, you know, he, he's sort of the spoiler.[00:38:25] NLW: Like people loved him just freestyle talking about why he thought they had a better headset than Apple. But even if they didn't agree, they just loved it. He was going direct to camera and talking about it for, you know, five minutes or whatever. So that, that's a fascinating shift that I don't think anyone had on their bingo card, you know, whatever, two years ago.[00:38:41] NLW: Yeah. Yeah,[00:38:42] swyx: we still[00:38:43] Alessio: didn't see and fight Elon though, so[00:38:45] swyx: that's what I'm really looking forward to. I mean, hey, don't, don't, don't write it off, you know, maybe just these things take a while to happen. But we need to see and fight in the Coliseum. No, I think you know, in terms of like self management, life leadership, I think he has, there's a lot of lessons to learn from him.[00:38:59] swyx: You know he might, you know, you might kind of quibble with, like, the social impact of Facebook, but just himself as a in terms of personal growth and, and, you know, Per perseverance through like a lot of change and you know, everyone throwing stuff his way. I think there's a lot to say about like, to learn from, from Zuck, which is crazy 'cause he's my age.[00:39:18] swyx: Yeah. Right.[00:39:20] AI Engineer landscape - from baby AGIs to vertical Agents[00:39:20] NLW: Awesome. Well, so, so one of the big things that I think you guys have, you know, distinct and, and unique insight into being where you are and what you work on is. You know, what developers are getting really excited about right now. And by that, I mean, on the one hand, certainly, you know, like startups who are actually kind of formalized and formed to startups, but also, you know, just in terms of like what people are spending their nights and weekends on what they're, you know, coming to hackathons to do.[00:39:45] NLW: And, you know, I think it's a, it's a, it's, it's such a fascinating indicator for, for where things are headed. Like if you zoom back a year, right now was right when everyone was getting so, so excited about. AI agent stuff, right? Auto, GPT and baby a GI. And these things were like, if you dropped anything on YouTube about those, like instantly tens of thousands of views.[00:40:07] NLW: I know because I had like a 50,000 view video, like the second day that I was doing the show on YouTube, you know, because I was talking about auto GPT. And so anyways, you know, obviously that's sort of not totally come to fruition yet, but what are some of the trends in what you guys are seeing in terms of people's, people's interest and, and, and what people are building?[00:40:24] Alessio: I can start maybe with the agents part and then I know Shawn is doing a diffusion meetup tonight. There's a lot of, a lot of different things. The, the agent wave has been the most interesting kind of like dream to reality arc. So out of GPT, I think they went, From zero to like 125, 000 GitHub stars in six weeks, and then one year later, they have 150, 000 stars.[00:40:49] Alessio: So there's kind of been a big plateau. I mean, you might say there are just not that many people that can start it. You know, everybody already started it. But the promise of, hey, I'll just give you a goal, and you do it. I think it's like, amazing to get people's imagination going. You know, they're like, oh, wow, this This is awesome.[00:41:08] Alessio: Everybody, everybody can try this to do anything. But then as technologists, you're like, well, that's, that's just like not possible, you know, we would have like solved everything. And I think it takes a little bit to go from the promise and the hope that people show you to then try it yourself and going back to say, okay, this is not really working for me.[00:41:28] Alessio: And David Wong from Adept, you know, they in our episode, he specifically said. We don't want to do a bottom up product. You know, we don't want something that everybody can just use and try because it's really hard to get it to be reliable. So we're seeing a lot of companies doing vertical agents that are narrow for a specific domain, and they're very good at something.[00:41:49] Alessio: Mike Conover, who was at Databricks before, is also a friend of Latentspace. He's doing this new company called BrightWave doing AI agents for financial research, and that's it, you know, and they're doing very well. There are other companies doing it in security, doing it in compliance, doing it in legal.[00:42:08] Alessio: All of these things that like, people, nobody just wakes up and say, Oh, I cannot wait to go on AutoGPD and ask it to do a compliance review of my thing. You know, just not what inspires people. So I think the gap on the developer side has been the more bottom sub hacker mentality is trying to build this like very Generic agents that can do a lot of open ended tasks.[00:42:30] Alessio: And then the more business side of things is like, Hey, If I want to raise my next round, I can not just like sit around the mess, mess around with like super generic stuff. I need to find a use case that really works. And I think that that is worth for, for a lot of folks in parallel, you have a lot of companies doing evals.[00:42:47] Alessio: There are dozens of them that just want to help you measure how good your models are doing. Again, if you build evals, you need to also have a restrained surface area to actually figure out whether or not it's good, right? Because you cannot eval anything on everything under the sun. So that's another category where I've seen from the startup pitches that I've seen, there's a lot of interest in, in the enterprise.[00:43:11] Alessio: It's just like really. Fragmented because the production use cases are just coming like now, you know, there are not a lot of long established ones to, to test against. And so does it, that's kind of on the virtual agents and then the robotic side it's probably been the thing that surprised me the most at NVIDIA GTC, the amount of robots that were there that were just like robots everywhere.[00:43:33] Alessio: Like, both in the keynote and then on the show floor, you would have Boston Dynamics dogs running around. There was, like, this, like fox robot that had, like, a virtual face that, like, talked to you and, like, moved in real time. There were industrial robots. NVIDIA did a big push on their own Omniverse thing, which is, like, this Digital twin of whatever environments you're in that you can use to train the robots agents.[00:43:57] Alessio: So that kind of takes people back to the reinforcement learning days, but yeah, agents, people want them, you know, people want them. I give a talk about the, the rise of the full stack employees and kind of this future, the same way full stack engineers kind of work across the stack. In the future, every employee is going to interact with every part of the organization through agents and AI enabled tooling.[00:44:17] Alessio: This is happening. It just needs to be a lot more narrow than maybe the first approach that we took, which is just put a string in AutoGPT and pray. But yeah, there's a lot of super interesting stuff going on.[00:44:27] swyx: Yeah. Well, he Let's recover a lot of stuff there. I'll separate the robotics piece because I feel like that's so different from the software world.[00:44:34] swyx: But yeah, we do talk to a lot of engineers and you know, that this is our sort of bread and butter. And I do agree that vertical agents have worked out a lot better than the horizontal ones. I think all You know, the point I'll make here is just the reason AutoGPT and maybe AGI, you know, it's in the name, like they were promising AGI.[00:44:53] swyx: But I think people are discovering that you cannot engineer your way to AGI. It has to be done at the model level and all these engineering, prompt engineering hacks on top of it weren't really going to get us there in a meaningful way without much further, you know, improvements in the models. I would say, I'll go so far as to say, even Devin, which is, I would, I think the most advanced agent that we've ever seen, still requires a lot of engineering and still probably falls apart a lot in terms of, like, practical usage.[00:45:22] swyx: Or it's just, Way too slow and expensive for, you know, what it's, what it's promised compared to the video. So yeah, that's, that's what, that's what happened with agents from, from last year. But I, I do, I do see, like, vertical agents being very popular and, and sometimes you, like, I think the word agent might even be overused sometimes.[00:45:38] swyx: Like, people don't really care whether or not you call it an AI agent, right? Like, does it replace boring menial tasks that I do That I might hire a human to do, or that the human who is hired to do it, like, actually doesn't really want to do. And I think there's absolutely ways in sort of a vertical context that you can actually go after very routine tasks that can be scaled out to a lot of, you know, AI assistants.[00:46:01] swyx: So, so yeah, I mean, and I would, I would sort of basically plus one what let's just sit there. I think it's, it's very, very promising and I think more people should work on it, not less. Like there's not enough people. Like, we, like, this should be the, the, the main thrust of the AI engineer is to look out, look for use cases and, and go to a production with them instead of just always working on some AGI promising thing that never arrives.[00:46:21] swyx: I,[00:46:22] NLW: I, I can only add that so I've been fiercely making tutorials behind the scenes around basically everything you can imagine with AI. We've probably done, we've done about 300 tutorials over the last couple of months. And the verticalized anything, right, like this is a solution for your particular job or role, even if it's way less interesting or kind of sexy, it's like so radically more useful to people in terms of intersecting with how, like those are the ways that people are actually.[00:46:50] NLW: Adopting AI in a lot of cases is just a, a, a thing that I do over and over again. By the way, I think that's the same way that even the generalized models are getting adopted. You know, it's like, I use midjourney for lots of stuff, but the main thing I use it for is YouTube thumbnails every day. Like day in, day out, I will always do a YouTube thumbnail, you know, or two with, with Midjourney, right?[00:47:09] NLW: And it's like you can, you can start to extrapolate that across a lot of things and all of a sudden, you know, a AI doesn't. It looks revolutionary because of a million small changes rather than one sort of big dramatic change. And I think that the verticalization of agents is sort of a great example of how that's[00:47:26] swyx: going to play out too.[00:47:28] Adept episode - Screen Multimodality[00:47:28] swyx: So I'll have one caveat here, which is I think that Because multi modal models are now commonplace, like Cloud, Gemini, OpenAI, all very very easily multi modal, Apple's easily multi modal, all this stuff. There is a switch for agents for sort of general desktop browsing that I think people so much for joining us today, and we'll see you in the next video.[00:48:04] swyx: Version of the the agent where they're not specifically taking in text or anything They're just watching your screen just like someone else would and and I'm piloting it by vision And you know in the the episode with David that we'll have dropped by the time that this this airs I think I think that is the promise of adept and that is a promise of what a lot of these sort of desktop agents Are and that is the more general purpose system That could be as big as the browser, the operating system, like, people really want to build that foundational piece of software in AI.[00:48:38] swyx: And I would see, like, the potential there for desktop agents being that, that you can have sort of self driving computers. You know, don't write the horizontal piece out. I just think we took a while to get there.[00:48:48] NLW: What else are you guys seeing that's interesting to you? I'm looking at your notes and I see a ton of categories.[00:48:54] Top Model Research from January Recap[00:48:54] swyx: Yeah so I'll take the next two as like as one category, which is basically alternative architectures, right? The two main things that everyone following AI kind of knows now is, one, the diffusion architecture, and two, the let's just say the, Decoder only transformer architecture that is popularized by GPT.[00:49:12] swyx: You can read, you can look on YouTube for thousands and thousands of tutorials on each of those things. What we are talking about here is what's next, what people are researching, and what could be on the horizon that takes the place of those other two things. So first of all, we'll talk about transformer architectures and then diffusion.[00:49:25] swyx: So transformers the, the two leading candidates are effectively RWKV and the state space models the most recent one of which is Mamba, but there's others like the Stripe, ENA, and the S four H three stuff coming out of hazy research at Stanford. And all of those are non quadratic language models that scale the promise to scale a lot better than the, the traditional transformer.[00:49:47] swyx: That this might be too theoretical for most people right now, but it's, it's gonna be. It's gonna come out in weird ways, where, imagine if like, Right now the talk of the town is that Claude and Gemini have a million tokens of context and like whoa You can put in like, you know, two hours of video now, okay But like what if you put what if we could like throw in, you know, two hundred thousand hours of video?[00:50:09] swyx: Like how does that change your usage of AI? What if you could throw in the entire genetic sequence of a human and like synthesize new drugs. Like, well, how does that change things? Like, we don't know because we haven't had access to this capability being so cheap before. And that's the ultimate promise of these two models.[00:50:28] swyx: They're not there yet but we're seeing very, very good progress. RWKV and Mamba are probably the, like, the two leading examples, both of which are open source that you can try them today and and have a lot of progress there. And the, the, the main thing I'll highlight for audio e KV is that at, at the seven B level, they seem to have beat LAMA two in all benchmarks that matter at the same size for the same amount of training as an open source model.[00:50:51] swyx: So that's exciting. You know, they're there, they're seven B now. They're not at seven tb. We don't know if it'll. And then the other thing is diffusion. Diffusions and transformers are are kind of on the collision course. The original stable diffusion already used transformers in in parts of its architecture.[00:51:06] swyx: It seems that transformers are eating more and more of those layers particularly the sort of VAE layer. So that's, the Diffusion Transformer is what Sora is built on. The guy who wrote the Diffusion Transformer paper, Bill Pebbles, is, Bill Pebbles is the lead tech guy on Sora. So you'll just see a lot more Diffusion Transformer stuff going on.[00:51:25] swyx: But there's, there's more sort of experimentation with diffusion. I'm holding a meetup actually here in San Francisco that's gonna be like the state of diffusion, which I'm pretty excited about. Stability's doing a lot of good work. And if you look at the, the architecture of how they're creating Stable Diffusion 3, Hourglass Diffusion, and the inconsistency models, or SDXL Turbo.[00:51:45] swyx: All of these are, like, very, very interesting innovations on, like, the original idea of what Stable Diffusion was. So if you think that it is expensive to create or slow to create Stable Diffusion or an AI generated art, you are not up to date with the latest models. If you think it is hard to create text and images, you are not up to date with the latest models.[00:52:02] swyx: And people still are kind of far behind. The last piece of which is the wildcard I always kind of hold out, which is text diffusion. So Instead of using autogenerative or autoregressive transformers, can you use text to diffuse? So you can use diffusion models to diffuse and create entire chunks of text all at once instead of token by token.[00:52:22] swyx: And that is something that Midjourney confirmed today, because it was only rumored the past few months. But they confirmed today that they were looking into. So all those things are like very exciting new model architectures that are, Maybe something that we'll, you'll see in production two to three years from now.[00:52:37] swyx: So the couple of the trends[00:52:38] NLW: that I want to just get your takes on, because they're sort of something that, that seems like they're coming up are one sort of these, these wearable, you know, kind of passive AI experiences where they're absorbing a lot of what's going on around you and then, and then kind of bringing things back.[00:52:53] NLW: And then the, the other one that I, that I wanted to see if you guys had thoughts on were sort of this next generation of chip companies. Obviously there's a huge amount of emphasis. On on hardware and silicon and, and, and different ways of doing things, but, y

古林は、エモさが溢れた時間に目頭が熱くなり、樋口は進化に心が踊っていた。 樋口は「セッションはコミュニケーションだ」と言い、そこに遠慮はいらないと感じる。 チバユウスケの魂は革ジャンに宿り、くちばしにPPAPなリョマたんの過去は本当なのか？ 言うことを聞かないダンシングクイーンは、強風でオールバックになりながらJAMを奏で、蟹を食べる旅に出かける。 【滉太郎】 【ITeens Lab 春の“宣伝してくだ祭”】 キャンペーン特設サイト⁠https://itl-2024spr.my.canva.site/⁠⁠ 特典カタログ ⁠https://itl-2024spr.my.canva.site/catalog⁠⁠ ITeens Lab公式WEBサイト⁠⁠https://iteenslab.com/⁠⁠⁠⁠ 「#新型オトナウィルス」でツイートお待ちしております。 【懺悔・お便りフォーム】 ⁠⁠⁠⁠ https://forms.gle/PpWNKHCFNYh1pF1t7⁠⁠⁠

On this episode, I outline an introduction to one of my favorite APQP tools, Production Part Approval Process(PPAP): - What is PPAP - Inputs, Process, Triggers and Interactions - PPAP Elements and Tools - The difference between first article inspection(FAI) and Capability Studies - Applications and Challenges in use Subhi Saadeh is a Quality Professional and host of the Combinate Podcast. With a background in Quality, Manufacturing Operations and R&D he's worked in Large Medical Device/Pharma organizations to support the development and launch of Hardware Devices, Disposable Devices, and Combination Products for Vaccines, Generics, and Biologics. Subhi serves currently as the International Committee Chair for the Combination Products Coalition(CPC) and as a member of ASTM Committee E55 and also served as a committee member on AAMI's Combination Products Committee. For feedback on the show or suggestions please contact subhi@letscombinate.com

ラックは、パスワード付きZIPファイルのメールを12月15日より原則廃止し、情報共有にクラウドストレージを活用すると発表した。

ANTARA - Pernahkah Sobat Antara mendengar tentang Pertukaran Pemuda Antar Provinsi atau PPAP? Ini adalah program yang dibentuk oleh Kementerian Pemuda dan Olahraga (Kemenpora) Republik Indonesia. Di tahun 2022 program ini kembali digelar pada dua titik yakni di Lumajang, Jawa Timur dan Manokwari, Papua Barat. Seperti apa tujuan kegiatan ini? Lalu, bagaimana kesan dan pengalaman yang dirasakan setelah kegiatan ini berakhir? Cari tahu jawabannya dalam episode ini. --- Send in a voice message: https://anchor.fm/antaranews-podcast/message

The grand return of your favorite anime podcast, the PPAP, is finally here just in time for spooky season! Join the usual gang as we discuss spies in a family, socially anxious rock girls, and a small indie anime named CHAINSAW MAN. Idk have you guys heard of that because I haven't? Make sure to like, comment, and subscribe and discuss what you think in the comments! TIMESTAMPS: 0:00 Intro 2:08 CHAINSAW MAN! 22:05 Spy X Family 26:40 Blue Lock 44:58 Mob Psycho 100 III 50:39 The Eminence in Shadow 1:00:00 Bleach TYBW 1:04:04 Akiba Maid War 1:12:00 Bocchi The Rock! 1:21:49 Urusei Yatsura 2022 1:30:55 Mobile Suit Gundam: The Witch from Mercury 1:34:22 Do It Yourself! 1:36:18 Outro Join our Discord: https://discord.gg/QRxcseETRK Hosts: Preston: https://myanimelist.net/profile/BladesNation Kevin: https://myanimelist.net/profile/Senhoegahara Carlo: https://myanimelist.net/profile/G1utenFreeWeen Jack: https://myanimelist.net/profile/TwistedRain

脱PPAPとして市場で提供されているサービスを「Webダウンロード方式」や「Webダウンロード + ワンタイムパスワード」等々、都合4つの方法を、A社 B社式に網羅的に挙げ、それぞれの方法の運用上の負荷や、排除できないリスクなどの懸念点を丁寧に分析する。

This week the team is recovering from DEFCON, purchasing Steam Decks, waxing nostalgic about PC building, and talking tech trash. 

ERP and contract management should be digital, but too many companies are still not streamlined and communicating with other businesses as effectively as possible. With the help of companies like Zumen, companies and computers are getting more connected and solving the issues that slow processes down. On this episode of The Digital Enterprise Society Podcast, Thom Singer and Craig Brown are joined by Viswa Kuppuswami, founder and CEO of Zumen, Inc., a SAAS startup product manufacturing company that focuses on managing the direct material procurement process. They discuss the importance of effective ERP (enterprise resource planning), overcoming and preventing supply chain issues, and how to automate workflows more effectively.    On today's podcast, you will learn: 3 critical systems to effective enterprise systems ERP software, according to Viswa and Craig, comes first.  Production planning and manufacturing processing comes next.  PLM or PDM is the third step, although ideally it would be first.  For growing and scaling companies, the first thing they need from a business perspective is a proper ERP system.   Streamlining the BOM-to-delivery process  Zumen focuses heavily on the new product processing.  As a product is designed and built, the accurate cost is also built into the product.  There can be an overlap as the product travels from design to supplier.  The product lifecycle and the procurement lifecycle both factor into a product entering the system.  Design changes from suppliers and designers are managed by the PRQ and RFQ.    Overcoming supply chain disruptions The ERP system is becoming more critical than ever as companies continue to adjust their supply chain processes.  More companies are identifying and appreciating the need for improved digitalization.  Proactive strategies need to be employed to prevent future shortages.  Digitized ERP systems can help companies identify their best options.    Automating workflows effectively  Companies need to be careful not to skip review steps along the way.  Digitized workflows can allow for a faster, but still as effective review process.  Considering the cost of disruption is an essential aspect of effective workflow.    Managing the parts library Companies need a robust framework for information digitalization.  Supply information and quality records are tracked and provided to companies.  Ppap information should be provided, with additional conversations happening as needed.    Continue the conversation with us within the Digital Enterprise Society Community at DigitalEnterpriseSociety.org.   Digital Download: Virtual Round-Table Series

ガクヅケ / 大人【コント】 https://youtu.be/qNe0TJw3CUc 4/25（月） 【ガクヅケのあつあつ新ネタやりやり配信ライブ2022】4月号 阿佐ヶ谷ロフトA 〈配信アーカイブ〉 通常1000円　応援1500円 ⚠️5/9（月）21:59まで購入可能 ⚠️5/9（月）23:59まで視聴可能 https://www.loft-prj.co.jp/schedule/lofta/210835 #ガクヅケ #お笑い #芸人 #2人組 #マセキ芸能社 #ピューと吹く！ジャガー #大塚愛 #ピロウズ #PPAP #アンパンマン #カニクリームコロッケ #蚊に食われる

祝 #セキュリティのアレ さん「サイバーセキュリティに関する総務大臣奨励賞」受賞、いかにもマルウェア添付してそうな日本語返信型スパムメールを隔離した、PPAPほぼ廃止、などについて話しました。

歩きながら録音する方がいろいろ楽、パスワード付きZIPファイルをメールに添付して送った後にパスワードを同じ宛先にメールで送ると受信者が誰でも復号できるよね、しかも暗号化ZIPはウィルススキャンできない、などについて話しました。

If you have been thinking about penetrating the automotive market, your customers will ask you to comply with the PPAP processes. You need to comply with several requirements irrespective of your tiers, such as communicating any process or line changes in your facility. You will also have additional testing requirements at the transaction level, such as corrosion testing, etc. If you don't understand these standards, you have a risk of losing your customer or wasting money on non-conforming parts.In today's episode, we have our guest, Ken Hatlewick, who discusses the nuances of the PPAP process for machine shops serving the automotive market. He also touches on the testing requirements at the transaction level and the audit and compliance requirements annually. Finally, he shares several stories about how upfront communication and relationships with your customer could help navigate issues if you run into challenges while complying with PPAP guidelines.For more information on growth strategies for SMBs using ERP and digital transformation, visit our community at wbs.rocks or elevatiq.com. To ensure that you never miss an episode of the WBS podcast, subscribe on your favorite podcasting platform.

ご意見・ご要望（フォーム） https://forms.gle/z4YN79Zj3iZch2Ri6 ／ ツイッター https://twitter.com/AsahiPodcast ・ https://twitter.com/fkuribayashi （栗林史子記者）／メール podcast@asahi.com （23分）ぺんぱいなっぽーあっぽーぺん…ではなく、「パスワードつき添付ファイル+パスワード別送」方式のメールのことです。面倒なだけでセキュリティー対策としての意味は薄いのでは、と指摘されています。大阪経済部の栗林史子記者に聞きました。※ピコ太郎さんが「PPAP」で話題になったのは2016年でした。 【関連記事】「PPAP」を廃止せよ　ピコ太郎じゃなくてメールの話（ https://www.asahi.com/articles/ASP7N5S4FP7HPLFA008.html?iref=omny ）▽ラジオは今も「お便りだけが頼りです」　ニッポン放送社長に聞いた（ https://www.asahi.com/articles/ASP9833WXP96UCVL01N.html?iref=omny ）▽企業の「紙」頼み　やめられたワケ、変われぬ事情（ https://www.asahi.com/articles/ASP8D73MMP8DULFA01M.html?iref=omny ） 朝日新聞ポッドキャスト（ https://www.asahi.com/special/podcasts/?iref=omny ）では他にも様々な番組を配信、テキストでも読めます。この番組は2021年8月20日に収録しました。 See omnystudio.com/listener for privacy information.

In this episode... Sofeast's CEO Renaud Anjoran is joined by Adrian from the team and they go through what deliverables buyers can expect to receive when working with suppliers during a new product development project in order to get safe, high-quality products into mass production. If you are developing a new product, you'll get a good grounding into what should be performed and documented during the process from product R&D through to mass production, including design files, the BOM, how to reduce risks, the control plan, inspections, pre-production validation testing, and more.   Show Notes 00:00 - Introduction.  01:03 - Going through the NPD process from the buyer's side and its deliverables in detail.  04:06 - The latest version of design files.  05:42 - The BOM.  07:28 - Risk mitigation.  09:28 - Elements and learnings from the automotive industry (PPAP).  10:49 - Risk analysis - FMEA on design & processes.  14:28 - The process flow chart/diagram.  15:55 - The control plan.  19:37 - Calibration or verification certificates of fixtures and instruments for checking quality.  21:44 - Product QC inspections. 23:31 - Pilot run stage - EVT, DVT, PVT. 28:03 - Engineering changes. 29:23 - Prototypes/tooling/PP samples. 31:44 - Does every type of part or product require such stringent deliverables?  33:45 - Wrapping up   Related content... Analysing the (NPI) New Product Introduction Process & its Benefits [Podcast] Why Pilot Runs Are A 'Must-Do' When Launching New Products [Podcast] NPI Process (New Product Introduction) NPD Project Constraints (3 common examples) Why You Need Mature Product Designs BEFORE Working With A Chinese Manufacturer! 3 Key Process Improvement Tools You Need To Start Using: Flow Chart, FMEA, Control Plan Developing New Products? Which Suppliers Are The Right Fit For You? The New Product Introduction Process For Hardware Startups [Guide]   Get in touch with us Connect with us on LinkedIn Send us a tweet @sofeast Prefer Facebook? Check us out on FB Contact us via Sofeast's contact page Subscribe to our YouTube channel   Subscribe to the podcast  There are more episodes to come, so remember to subscribe! You can do so in your favorite podcast apps here and don't forget to give us a 5-star rating, please: Apple Podcasts Spotify Stitcher Google Podcasts TuneIn Deezer iHeartRADIO PlayerFM Listen Notes Podcast Addict

医療システムに不正アクセス、撮影画像が閲覧不能に - 市立東大阪医療センター　メールアドレス流出、自動PPAP機能に不具合 - 原子力規制委　ほか

PPAP廃止後のメール誤送信防止市場、2桁増の見込み by bp-Affairs

Pour célébrer le mois de la bande dessinée; on consacre l’escale du bourlingueur à la dessinatrice  Sylvie-Anne Ménard qui a publié aux éditions Pow Pow une bande dessinée qui relate son voyage au Japon ! Une belle façon de raconter ses aventures à Kyoto ! On parlera aussi de son passage à Angoulême durant le festival de la bande dessinée.   Chansons au programme :  - PPAP, de Pikotaro - Kaimono Boogie, de Kasagi Shizuko - La toune de l'opening de Cutie Honey, de 1973 - Insatiable high - Masayoshi Takanaka - Coral Reef, de Haruomi Hosono Sites de référence : https://editionspowpow.com/boutique/zviane-au-japon/

#時事ネタ

Googleサーバー障害、LINEロゴ変わった？、EchoShowでNetflix、鬼滅の刃の興行収入、車載Wi-Fi、PPAP、1917、ゲーム会社の安全に係る協定などについて話しました。 Show Notes Pio ...

W dzisiejszym odcinku odpowiadam na pytania Damiana - jak przeprowadzić audyt dostawcy oraz co zrobić przy rozterkach dotyczących PPAP. Jeżeli ty masz pytania, to napisz do mnie arturmydlarz@inzynierjakosci.pl . Odpowiem w formie podcastu. Linki do polecenia: 1) https://www.szkolajakosci.pl 2) https://www.inzynierjakosci.pl

DX(デジタルトランスフォーメーション)についてAI・IoT教育の専門家、近森満が語ります。今回は、平井卓也デジタル改革担当相による霞が関におけるPPAP廃止宣言による話題の「PPAP(パスワード付きZIPファイル)」廃止について、諸々の弊害やメリットについてお話いたします。

一般財団法人日本情報経済社会推進協議会（JIPDEC）は11月18日、個人情報を含むファイル等のメール送信時に、ファイルをパスワード設定で暗号化して添付し、そのパスワードを別メールで送信する行為について、JIPDECは推奨していないと明言した。

DX番外編37：今旬なキーワード「PPAPを廃止」について解説しました。「平井卓也デジタル改革担当相は11月17日の定例会見で、中央省庁の職員が文書などのデータをメールで送信する際に使うパスワード付きzipファイルを廃止する方針である」というニュースから、PPAPってなに？という素朴な疑問に答えています。

ついに霞ヶ関が動きます！無意味と言われ続けていたセキュリティポリシーPPAPが廃止となります。さて、PPAPとは？詳しくはVoicyのダジャレITパパニュースへ！https://voicy.jp/channel/181/108981 --- Send in a voice message: https://anchor.fm/itpapanews/message

OUR 2ND EPISODE IS HERE!!! If you haven't done so already, please check out our first impressions video that came out before this one. Today on the PPAP, we're going over our FINAL Impressions on the anime that aired during the Summer 2020 season. Did our opinions on Re: Zero change throughout the course of season 2? Was Deca-Dence the most slept on anime of the year? Join us as we discuss the highs and lows of Summer 2020 as well as our favorite anime of the season. Don't forget to like, comment, and subscribe. Hope you enjoy! Join our Discord! https://discord.gg/qQTfUvj Listen To Us On Spotify: https://open.spotify.com/show/1seyxnH... Follow Us On Twitter: https://mobile.twitter.com/anime_ppap Hosts: Preston: https://myanimelist.net/profile/Blade... Kevin: https://myanimelist.net/profile/Senho... Jack: https://myanimelist.net/profile/Twist... Carlo: https://myanimelist.net/profile/G1ute..

Zapraszam na świetną rozmowę z Michałem Jezuskiem na temat budowania kariery w zarządzaniu jakością w branży Automotive. Michał rozpoczynał jako stażysta, a po 5 latach ma już za sobą kilka awansów, międzynarodowe projekty i wkrótce rozpocznie pracę jako wykładowcą na Uniwersytecie Ekonomicznym. Co ciekawe Michał dołączył również do Szkoły Jakości   i możecie go znać jako mentora kursu PPAP. Niezbędne linki: https://szkolajakosci.pl/ http://inzynierjakosci.pl/

フォローやいいねをしていただけると喜びます☺️ お便りやギフトも喜びます 火曜水曜木曜金曜日曜20時30分頃〜RadiotalkでLIVEする予定です！ 毎週土曜遅くても20時頃からニャブリ会(LIVE)。詳しくは #22 https://radiotalk.jp/talk/386761 TwitterとInstagramも、フォローよろしくお願いします！ http://twitter.com/@shochannoradio https://peing.net/shochannoradio https://www.instagram.com/sho5baty37 #ショウちゃん #海外から配信 #ドイツ #サッカー #サッカー選手 #ドイツサッカー #PPAP #イタリア人

いやー今月はなんとか毎週配信に復活したかったけど3本しか公開できなんだ。なかなか時間がとれませんなあ。 さて今回は、なんか情報セキュリティ業界の一部が、今までと逆のことをいいはじめましたよ？という話題。メールの添付ファイルにパスワードってかけてますか？そしてそれって正しいことですか？ 関連リンク: 日曜劇場『半沢直樹』｜TBSテレビ スネークマンショー - Wikipedia S/MIME - Wikipedia Pretty Good Privacy - Wikipedia セキュリティ的に意味なし　“旧ノーマル”な職場にはびこる習慣、その名も「PPAP」を知っていますか (1/2) - ITmedia エンタープライズ Music From: mylostbeat / tylersrevenge (CC-by) U R A DJ * / Portamentor (CC-by) A Little Bit Of Everything Jam / Synthdrumnoise (CC-by) Robowalk / sausageblowfly (CC-by) Four / ArtisFeeling (CC-by)

PINEAPPLE PEN GUY Before They Were Famous - The Pineapple Pen is performed by a guy in Japan named Kuzuhito Kosaka but he goes by the name DJ Kosaka Daimao and then the character in the video is named Piko-taro. Find out everything there is to know about this guy here on Before They Were Famous.

PPAP to podstawowe narzędzie do zatwierdzania procesu produkcyjnego w branży Automotive. Dlatego do rozmowy zaprosiłem eksperta z 15-letnim doświadczeniem Agatę Lewkowską. Dowiedz się, czym jest PPAP i jakich błędów nie popełniać linki: https://inzynierjakosci.pl/2017/12/ppap-automotive-proces-opis/ https://szkolajakosci.pl/ http://inzynierjakosci.pl/

A morning edition where I talk about the day to come.

Today I talk about my PPAP findings, month end, and other random ramblings.

On the show tonight appearing @Packard_Sonic, as your host co-host Atheist Ranger @Antonio_Prous & Matt Gillmore.  Call our voice mail at 662-709-PPAP or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please subscribe and hit the thumbs up! Thanks! Download PPAP S10E05: Ham, Hell and Pizza Rolls MP3 You can hear Packard Pokes At while … Continue reading PPAP S10E05: Ham, Hell and Pizza Rolls

On the PPAPodcast @Packard_Sonic, as your host & co-hosts Atheist Ranger & Matt Notabeliver71. Call our voice mail at 662-709-PPAP  or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please feel free to hit the donate button and give what you can or what you feel the show is worth to you. Download PPAP … Continue reading PPAP S10E04: OK, Let’s Talk: No Sacred Cows: Are All Fair Game Or Not?

On the show tonight appearing @Packard_Sonic, as your host co-host Atheist Ranger @Antonio_Prous & Matt Gillmore.  Call our voice mail at 662-709-PPAP or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please subscribe and hit the thumbs up! Thanks! Download PPAP S10E03: Religion’s Attack On Humanity MP3 You can hear Packard Pokes At while on … Continue reading PPAP S10E03: Religion’s Attack On Humanity

On the show tonight appearing @Packard_Sonic, as your host co-host Atheist Ranger @Antonio_Prous & Matt Gillmore.  Call our voice mail at 662-709-PPAP or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please subscribe and hit the thumbs up! Thanks! Download PPAP S10E02: Don’t Inject Semen, Because Jesus Told Me To MP3 You can hear Packard … Continue reading PPAP S10E02: Don’t Inject Semen, Because Jesus Told Me To

On the PPAPodcast @Packard_Sonic, as your host & co-hosts Atheist Ranger & Matt Notabeliver71. Call our voice mail at 662-709-PPAP  or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please feel free to hit the donate button and give what you can or what you feel the show is worth to you. Download PPAP … Continue reading PPAP S10E01: OK, Let’s Talk: Religion Pays Off: A Grifters Paradise

On the PPAPodcast @Packard_Sonic, as your host & co-hostsAtheist Ranger & @Antonio_Prous, & Matt NotABeliever71. Call our voice mail at 662-709-PPAP  or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please feel free to hit the donate button and give what you can or what you feel the show is worth to you. Download … Continue reading PPAP S09E02: OK, Let’s Talk: Old Crazy Christians And The BS They Tell

This is a raw unedited recording of our weekly staff meeting for the show. Call our voice mail at 662-709-PPAP or 662-709-7727. Download PPAP 09E01: The Staff meeting MP3 No show notes The show is also available on YouTube at http://youtube.com/PackardPokesAt Looking forward to see your comments there as well. Please subscribe and hit the … Continue reading PPAP S09E01: The Staff meeting

On the PPAPodcast @Packard_Sonic, as your host, with co-hosts Atheist Ranger & @Antonio_Prous, & Matt NotABeliever71. The live show that starts at 8 PM CDT (Central Daylight Time). Call our voice mail at 662-709-PPAP  or 662-709-7727. You can find the live show at http://youtube.com/PackardPokesAt. Please donate and give what you can to help support the show. … Continue reading PPAP S08E28: Conspiracy Theorist Needs A Spanking!!

This week, the largest hack of all time, Twitter & SoundCloud may have new owners, Apple plans its own version of the Echo, Snapchat makes a Spectacle of itself, Humans are one flight closer to Mars ... and much, much more.   Headlines Yahoo confirms major breach — and it could be the largest hack of all time Defending Against Hackers Took a Back Seat at Yahoo, Insiders Say Twitter may soon get formal bid, suitors said to include Salesforce and Google Disney Is Working With an Adviser on Potential Twitter Bid Spotify in Talks to Acquire SoundCloud Audible Book of the Week Our Final Invention: Artificial Intelligence and the End of the Human Era by James Barrat Sign up at AudibleTrial.com/TheDrillDown Music Break: Telephone by Pomplamoose Hot Topic: The Decline of Mobile Apple Stepping Up Plans for Amazon Echo-Style Smart-Home Device Apple iPhone 7 Sales Hide a Serious Problem The global smartphone boom is over — sorry Apple BlackBerry bails on building its own phones Snapchat unveils $130 connected sunglasses and rebrands as Snap, Inc. Music Break: Mars: The Bringer of War by Gustav Holst Final Word: To Mars! Elon Musk lays out his vision for a human civilization on Mars The Drill Down Videos of the Week SpaceX Interplanetary Transport System PPAP Pen Pineapple Apple Pen How a 'Pen-Pineapple-Apple-Pen' earworm took over the internet Internet goes crazy for pineapple pen Subscribe! The Drill Down on iTunes (Subscribe now!) Add us on Stitcher! The Drill Down on Facebook The Drill Down on Twitter Geeks Of Doom's The Drill Down is a roundtable-style audio podcast where we discuss the most important issues of the week, in tech and on the web and how they affect us all. Hosts are Geeks of Doom contributor Andrew Sorcini (Mr. BabyMan), marketing research analyst Dwayne De Freitas, and Box product manager Tosin Onafowokan.