Generic ghosts and vague vampires haunted the Hollywood picket lines this Halloween, as striking actors tried to scare studio bosses by refusing to dress up as any of their famous characters. With talks still ongoing between the Screen Actors Guild (SAG ...

Halloween hits Hollywood strike as actors boycott Barbie costumes

While artificial intelligence promises to transform society in major ways, driverless taxis offer a stark example of the bumpy road the technology faces before it reaches its potential. In California, for example, a serious collision involving a robotaxi is forcing the state to reevaluate its growing push into driverless technology.

A robotaxi, a collision, and the bumpy road to an AI future

Christina Ricci "wanted to marry" Matthew Perry when she was a teenager and cried when she heard the 'Friends' star had died.

Christina Ricci 'wanted to marry' Matthew Perry

Matthew Perry's 'Friends' co-star Lisa Kudrow is said to be "considering" adopting the late actor's beloved dog Alfred. The main 'Friends' cast, including the Phoebe Buffay actress, is yet to break their silence on Matthew's heartbreaking sudden death aged 54 on Saturday (28.10.23), however, they are said to be in a state of "total shock".

'Baffled' Lisa Kudrow reportedly wants to adopt late Friends co-star Matthew Perry's dog

Joe Thornton has officially announced his retirement from the NHL following a 24-year career as one of the game’s top playmakers. The 44-year-old Thornton hadn’t played since the 2021-22 season

Joe Thornton officially retires from the NHL after a 24-year career

The map shows every autonomous-vehicle crash in The City from Oct., 2014 to July, 2023, most of which are concentrated in The City’s northeast corridor. The Examiner is still awaiting data from August to the present. The map will be updated when we hear back.

Map shows every autonomous-vehicle crash in San Francisco since 2014

The company is suspending its operations of autonomous vehicles without human supervision after regulators expressed concerns, but will continue human supervised operations.

Cruise suspends driverless operations

Linda said this may become a "full opportunity" in 2024. "It would blow my mind if we don’t have that rolled out by the end of next year," Musk added.

I'll make X the centre of people’s financial lives: Musk tells staff

Driverless car company Cruise is to pause self-driving operations across its fleet, days after California regulators barred its vehicles from the state’s roads.

GM’s Cruise to suspend all driverless car fleets after California ban

Cruise suspended its driverless robotaxis nationwide two days after losing its self-driving permit in San Francisco for an incident in which a pedestrian was trapped under an autonomous vehicle.

GM’s Cruise Halts All US Robotaxi Service After Suspension for Pedestrian Who Was Dragged

Zoox

zoox

Why is Tesla's coming Robotaxi such a big deal? Uber was partially invented right in front of me in a Paris snowstorm by Garrett Camp and Travis Kalanick. That set me on a path of understanding Transportation as a Service, which really is what Uber is. You order a ride on a computer, usually your phone, and one arrives. If I want to take one to San Francisco Airport it usually costs around $70 for an hour drive from my home in San Jose. Uber grew from that Paris snowstorm to being in many countries within three years. Uber is, so far, human driven. Humans have some advantages, they come with their own cars, so Uber didn't need to take on any inventory risk. But they come with many disadvantages too. Some talk too much. Some smell. Even of weed. Some arrive inebriated. Some abuse their riders, or worse. Yes, most of the time a great human shows up with a new model car that's well maintained and clean, but use Uber all around the world, like I have, and you'll hit these problems. Inconsistencies. And notice we haven't talked about how much the human costs, either in dollars (minimum wage is about $20 in California) or in safety costs (human tragedy in cars is pretty frequent, with around 40,000 deaths in USA every year alone). While a new Tesla costs about $3 to sit in your driveway every hour, add a human and the cost runs much more. Go back to Elon's first sales pitch (he gave it to me personally at the beginning) and he talked about beating legacy auto on price and experience. He's been planning Robotaxi since before the Model 3 shipped in 2017. How do I know that? Because only his cars have electric vents, something that still gets him derided. Mercedes engineers told me personally ts customers hated electric vents, and that they wanted knobs instead. But it is the electric vents that will give you a better experience, along with a number of other things, including a better audio system than the others have. But compared to the others it will have a better brand due to this focus on experience and consistency. What makes a great brand? Not, necessarily having the best product. Starbucks, for instance, doesn't, and I can find you better things to drink than Coke, but those two are great brands because they are consistent and ubiquitous. So, why does Tesla matter here? What about Waymo, Zoox, Cruise, or a handful of other potential Robotaxi competitors? What is its moat? Years ago I did consumer research, going around America asking people "are you willing to get into a vehicle that has no steering wheel?" Most answered "f**k no." I have studied several technological paradigm shifts and heard protests every time, but this was the most adamant of my career. I was talking about this with Peter Norvig, who used to play a key role at Google R&D and claims he is the guy who got the funding to start its autonomous vehicle project, about this. He told me Google already had the data to know that after three rides in a Waymo they will deeply trust autonomous vehicles to the point that they will want to use them for every ride. It is this key point "use them for every ride" that gets execs and investors interested in autonomous vehicles. I've heard this too from many San Francisco residents who love Waymo's service of being able to hop into an autonomous vehicle. But why does Tesla matter? Tesla's AI started out behind Waymo/Google's but has been learning faster. I believe that it is already better than Waymo at generalization (Waymo is only available in a few cities while my Tesla drove me 900 miles to Sun Valley from my home in San Jose). Yaman had an excellent show with Omar of Whole Mars Catalog that everyone should watch that compares Waymo and Tesla. Already Tesla's AI is smoother in many places. Back to the point. If you arrive in Las Vegas for a conference or on vacation which one do you choose to use? Tesla? Waymo? Zoox? Cruise? Uber? Lyft? Or some other brand or taxi? My prediction is that Tesla will win most of this business in 2030. Why? Experience. Being in a Tesla vehicle is safer in a crash than the vehicles that the other companies use.


Being in a Tesla will have a better experience, from the vents to the sound system.


Using a Tesla will be more consistent. Everyone knows what ordering a Cybertruck will do. Taxis and Uber always shows up with different vehicles so won't be as consistent. Starbucks shows that people will choose a consistent product over one that's better quality, but isn't as consistent. But it is the fleet size that really matters. When I interviewed Travis Kalanick, Uber's founder, in front of Stanford Business School, he told me that he had one big goal: to have a vehicle near you so that when you ordered one, it only took a few minutes to show up. If three vehicles were waiting nearby then the drivers weren't being used efficiently, pissing them off for not getting paid. If none are nearby then it takes too long for a vehicle to get to you. So who has the biggest fleet? Of autonomous vehicles? None of them other than Tesla is on my street and on my street there are 13 Teslas already. So many that I can walk to another Tesla in seconds. Faster than I could get one in San Francisco. It wouldn't even need to drive to me! The fleet size matters in many other ways, particularly experience. Why? Well, let's say there are a bunch of Teslas on the road in front of you. They can "see" all sorts of things, from fires, to protests, to police actions, and can report those to the control system that runs the network. So it could route around problems faster than any other network. That makes the experience better. If you can see that it has real-time info, you will learn to trust the one that has the real-time info on the screen more than one that doesn't have as much info. Which gets us to another thing. All us Tesla owners have its app running on our phones. That could feed a lot of new data into the network, like about how busy a nightclub or a restaurant is. Or details about a news event. Literally none of us have a Waymo app on our phones. Most humans haven't even heard of, or seen, a Waymo. Uber? Sure! But it comes with a human which brings the above problems and a higher price. Speaking of price. A Waymo has quite a few expensive LiDARs and more compute on board than Tesla does to handle both camera feeds and LiDAR feeds. Tesla has gone with a camera only approach, which is not only cheaper per vehicle, but looks a lot nicer too and can be hidden inside a standard-looking vehicle. Waymo's have gotten vandalized several times because they are the symbols of a new, dystopian, age, as one of my friends put it. Tesla's just are everywhere in many cities, especially anyone near San Francisco so won't attract the same kind of attention. So, my predictions: By 2030: Tesla robotaxi will be cheaper than other networks. Tesla will have a better screen and audio system for you to use. Movies, education, music, video conference calls, etc, will be better in a Tesla and more consistent. Tesla will be safer, and go more places. Tesla's route picker will be way better. Especially around massive events like concerts, sporting events, and more. Tesla's vents, seats, mirrors, audio level, are automatically set to personalize to you. Tesla's app and vehicles gives you more details, which leads to a better experience "there's a 14-minute line at the McDonalds." Let's put it bluntly: Tesla's customer acquisition cost will be nearly zero, while Waymo or Zoox will need to spend a lot more to create both awareness and behavior. I don't think they will be able to convince a Tesla user to switch to their platforms given the better experience and lower price I'm expecting Tesla to have. To wrap it up, for now, let's say you want to take your lover to a downtown for a date night. In an Uber there is a driver taking up one of the two best seats. In a Tesla? Nope. So date night is way better. On Thursday night we'll see just how much better. Why is Tesla's coming Robotaxi such a big deal? Uber was partially invented right in front of me in a Paris snowstorm by Garrett Camp and Travis Kalanick. That set me on a path of understanding Transportation as a Service, which really is what Uber is. You order a ride on a computer, usually your phone, and one arrives. If I want to take one to San Francisco Airport it usually costs around $70 for an hour drive from my home in San Jose. Uber grew from that Paris snowstorm to being in many countries within three years. Uber is, so far, human driven. Humans have some advantages, they come with their own cars, so Uber didn't need to take on any inventory risk. But they come with many disadvantages too. Some talk too much. Some smell. Even of weed. Some arrive inebriated. Some abuse their riders, or worse. Yes, most of the time a great human shows up with a new model car that's well maintained and clean, but use Uber all around the world, like I have, and you'll hit these problems. Inconsistencies. And notice we haven't talked about how much the human costs, either in dollars (minimum wage is about $20 in California) or in safety costs (human tragedy in cars is pretty frequent, with around 40,000 deaths in USA every year alone). While a new Tesla costs about $3 to sit in your driveway every hour, add a human and the cost runs much more. Go back to Elon's first sales pitch (he gave it to me personally at the beginning) and he talked about beating legacy auto on price and experience. He's been planning Robotaxi since before the Model 3 shipped in 2017. How do I know that? Because only his cars have electric vents, something that still gets him derided. Mercedes engineers told me personally ts customers hated electric vents, and that they wanted knobs instead. But it is the electric vents that will give you a better experience, along with a number of other things, including a better audio system than the others have. But compared to the others it will have a better brand due to this focus on experience and consistency. What makes a great brand? Not, necessarily having the best product. Starbucks, for instance, doesn't, and I can find you better things to drink than Coke, but those two are great brands because they are consistent and ubiquitous. So, why does Tesla matter here? What about Waymo, Zoox, Cruise, or a handful of other potential Robotaxi competitors? What is its moat? Years ago I did consumer research, going around America asking people "are you willing to get into a vehicle that has no steering wheel?" Most answered "f**k no." I have studied several technological paradigm shifts and heard protests every time, but this was the most adamant of my career. I was talking about this with Peter Norvig, who used to play a key role at Google R&D and claims he is the guy who got the funding to start its autonomous vehicle project, about this. He told me Google already had the data to know that after three rides in a Waymo they will deeply trust autonomous vehicles to the point that they will want to use them for every ride. It is this key point "use them for every ride" that gets execs and investors interested in autonomous vehicles. I've heard this too from many San Francisco residents who love Waymo's service of being able to hop into an autonomous vehicle. But why does Tesla matter? Tesla's AI started out behind Waymo/Google's but has been learning faster. I believe that it is already better than Waymo at generalization (Waymo is only available in a few cities while my Tesla drove me 900 miles to Sun Valley from my home in San Jose). Yaman had an excellent show with Omar of Whole Mars Catalog that everyone should watch that compares Waymo and Tesla. Already Tesla's AI is smoother in many places . smoother in many places Back to the point. If you arrive in Las Vegas for a conference or on vacation which one do you choose to use? Tesla? Waymo? Zoox? Cruise? Uber? Lyft? Or some other brand or taxi? My prediction is that Tesla will win most of this business in 2030. Why? Experience. Being in a Tesla vehicle is safer in a crash than the vehicles that the other companies use. Being in a Tesla will have a better experience, from the vents to the sound system. Using a Tesla will be more consistent. Everyone knows what ordering a Cybertruck will do. Taxis and Uber always shows up with different vehicles so won't be as consistent. Starbucks shows that people will choose a consistent product over one that's better quality, but isn't as consistent. Being in a Tesla vehicle is safer in a crash than the vehicles that the other companies use. Being in a Tesla vehicle is safer in a crash than the vehicles that the other companies use. Being in a Tesla will have a better experience, from the vents to the sound system. Being in a Tesla will have a better experience, from the vents to the sound system. Using a Tesla will be more consistent. Everyone knows what ordering a Cybertruck will do. Taxis and Uber always shows up with different vehicles so won't be as consistent. Starbucks shows that people will choose a consistent product over one that's better quality, but isn't as consistent. Using a Tesla will be more consistent. Everyone knows what ordering a Cybertruck will do. Taxis and Uber always shows up with different vehicles so won't be as consistent. Starbucks shows that people will choose a consistent product over one that's better quality, but isn't as consistent. But it is the fleet size that really matters. When I interviewed Travis Kalanick, Uber's founder, in front of Stanford Business School, he told me that he had one big goal: to have a vehicle near you so that when you ordered one, it only took a few minutes to show up. If three vehicles were waiting nearby then the drivers weren't being used efficiently, pissing them off for not getting paid. If none are nearby then it takes too long for a vehicle to get to you. So who has the biggest fleet? Of autonomous vehicles? None of them other than Tesla is on my street and on my street there are 13 Teslas already. So many that I can walk to another Tesla in seconds. Faster than I could get one in San Francisco. It wouldn't even need to drive to me! The fleet size matters in many other ways, particularly experience. Why? Well, let's say there are a bunch of Teslas on the road in front of you. They can "see" all sorts of things, from fires, to protests, to police actions, and can report those to the control system that runs the network. So it could route around problems faster than any other network. That makes the experience better. If you can see that it has real-time info, you will learn to trust the one that has the real-time info on the screen more than one that doesn't have as much info. Which gets us to another thing. All us Tesla owners have its app running on our phones. That could feed a lot of new data into the network, like about how busy a nightclub or a restaurant is. Or details about a news event. Literally none of us have a Waymo app on our phones. Most humans haven't even heard of, or seen, a Waymo. Uber? Sure! But it comes with a human which brings the above problems and a higher price. Speaking of price. A Waymo has quite a few expensive LiDARs and more compute on board than Tesla does to handle both camera feeds and LiDAR feeds. Tesla has gone with a camera only approach, which is not only cheaper per vehicle, but looks a lot nicer too and can be hidden inside a standard-looking vehicle. Waymo's have gotten vandalized several times because they are the symbols of a new, dystopian, age, as one of my friends put it. Tesla's just are everywhere in many cities, especially anyone near San Francisco so won't attract the same kind of attention. So, my predictions: By 2030: Tesla robotaxi will be cheaper than other networks. Tesla will have a better screen and audio system for you to use. Movies, education, music, video conference calls, etc, will be better in a Tesla and more consistent. Tesla will be safer, and go more places. Tesla's route picker will be way better. Especially around massive events like concerts, sporting events, and more. Tesla's vents, seats, mirrors, audio level, are automatically set to personalize to you. Tesla's app and vehicles gives you more details, which leads to a better experience "there's a 14-minute line at the McDonalds." Let's put it bluntly: Tesla's customer acquisition cost will be nearly zero, while Waymo or Zoox will need to spend a lot more to create both awareness and behavior. I don't think they will be able to convince a Tesla user to switch to their platforms given the better experience and lower price I'm expecting Tesla to have. To wrap it up, for now, let's say you want to take your lover to a downtown for a date night. In an Uber there is a driver taking up one of the two best seats. In a Tesla? Nope. So date night is way better. On Thursday night we'll see just how much better.

How Tesla's Positioned to Win the Robotaxi Market By 2030 Over Waymo, Zoox, Cruise, Uber, and Lyft

كيف يمكن لشركة Tesla الفوز بسوق سيارات الأجرة الآلية بحلول عام 2030 على حساب Waymo وZoox وCruise وUber وLyft

So positioniert sich Tesla, um bis 2030 den Robotaxi-Markt vor Waymo, Zoox, Cruise, Uber und Lyft zu erobern

Cómo se posiciona Tesla para ganar el mercado de robotaxi en 2030 frente a Waymo, Zoox, Cruise, Uber y Lyft

Como se posiciona Tesla para gañar o mercado de Robotaxi para 2030 sobre Waymo, Zoox, Cruise, Uber e Lyft

Bagaimana Tesla Diposisikan untuk Memenangkan Pasar Robotaxi pada Tahun 2030 Mengalahkan Waymo, Zoox, Cruise, Uber, dan Lyft

テスラは2030年までにウェイモ、ズークス、クルーズ、ウーバー、リフトを抑えてロボタクシー市場を制覇する立場にある

Тесла 2030-жылга чейин Роботакси рыногун Waymo, Zoox, Cruise, Uber жана Lyft аркылуу кантип утуп алды

Bagaimana Tesla Kedudukan untuk Memenangi Pasaran Robotaxi Menjelang 2030 Berbanding Waymo, Zoox, Cruise, Uber dan Lyft

Hoe Tesla zich positioneert om de markt voor robotaxi's in 2030 te veroveren ten koste van Waymo, Zoox, Cruise, Uber en Lyft

Ukuntu Tesla ihagaze kugirango itsinde isoko rya Robotaxi Muri 2030 hejuru ya Waymo, Zoox, Cruise, Uber, na Lyft

Paano Nakaposisyon ang Tesla na Manalo sa Robotaxi Market Pagsapit ng 2030 Sa Waymo, Zoox, Cruise, Uber, at Lyft

Tesla 2030 yilga kelib Robotaxi bozorini Waymo, Zoox, Cruise, Uber va Lyft orqali qanday qilib yutib oladi

Here's a new problem, and a new set of jobs for humans, that will be caused as more and more Robotaxis show up (think of an Uber that works without a human in the car). What is the problem? Transportation behavior will change as we get more and more vehicles on the road with no humans inside. Something that's already happening in San Francisco, where you see many autonomous vehicles driving around with no humans inside from companies like Waymo, Zoox, and others. Expected are many others, including Tesla, and GM's Cruise which we hear will be back on the road later this year. The problem? Football stadiums, concerts, basketball stadiums, conferences, events like the Olympics, all will see radically different usage patterns. For instance, today, if you attend a football game, you park in one of dozens of parking lots around the stadium and you walk in, or take a shuttle to one of the entrances. This adds some "randomness" to the flow of crowds in and out and lets city officials who plan out traffic flows bring traffic to those parking lots with a few different routes. Even today it's often a mess with traffic taking an hour to get into many venues with large numbers of people but officials, and others, who work in these industries tell me autonomous vehicles will make traffic far worse. Why? Well, let's assume in five years you are in a Cybertruck taking your family to a football game and that by then the Cybertruck can drive with no humans in the car. Will you want your Cybertruck to take you to a far off parking lot and make you walk to the stadium? No. You'll want it to drop you off near the football stadium. And here's the rub: so will everyone else. Which means you'll have thousands of Waymos, Cruises, Teslas, all trying to get to the same drop-off point. This new human expectation will lead to traffic nightmares. Worse, I've been talking with executives at these kinds of venues and they say the coordination between sports teams, city officials/police, and ride-sharing companies is nearly non-existent.One told me they tried to get Uber and Lyft to come meet with them to design new traffic flows for their vehicles and they just don't get very little help or interest from the ride-sharing companies. One, who works with the 49ers, tells me city officials often put up signs for Uber/Lyft drivers that lead them into dead-end roads where they need to waste time turning around and figuring out where they need to go. Signage, cones, road closures, all could be done in a much better way around venues. And that's before you consider the humans. Often crowds of humans getting out of venues are drunk, don't follow traffic rules, and, sometimes, even turn riotous. Has the autonomous vehicle industry worked with venues to understand how traffic systems change around event venues? No, is the answer I keep hearing, and getting Waymo or Tesla interested in studying the problem together and designing new traffic facilities around big-crowd venues is difficult. Oh, it can happen. At Coachella, for instance, Uber built a huge parking lot with waiting areas for humans that were covered (it's hot often waiting for your ride to show up). Uber also built contextual systems to work with drivers around the Western United States to convince drivers to come to Palm Springs for a month and drive people around (Coachella is two weekends, where 150,000 people visit each weekend, followed by a country music festival that has slightly smaller crowds, but Uber, alone, brings thousands of cars to handle the crowds of people who want to use it to get to and from the venue). Along with the parking lot city officials block off lanes and have clear signs for Uber/Lyft/Taxis to use and have police at every intersection directing traffic and making sure things flow smoothly. Even with all that work it often takes one to three hours of standing in line to get a Taxi or an Uber out of the venue. Now imagine if thousands of people were arriving in autonomous vehicles. If the vehicles weren't programmed into where to go, and if Tesla doesn't have its own drop off and pickup lot things could get nasty, and fast. Last week at NVIDIA's big event my Tesla was programmed to pick up a friend at the Marriott. Problem was it took me down a route that is usually just fine, but during that event NVIDIA and city officials had the street in front of the conference center closed due to the large crowds that were attending that event. My Tesla didn't know about the closed street so it tried to take me down that closed street, figured it out too late, and then got stuck in traffic going on a detour around, wasting 15 minutes. Now 15 minutes doesn't seem like a big deal, but it is if I was driving an Uber passenger. Why? Well, first of all now I have a passenger who isn't happy with the navigation choices the car made, maybe giving me a lower score than I otherwise would get, but, worse, if I was picking up a passenger that person might see that I'm now 15 minutes away instead of two and decide to hop in a cab or cancel my ride. Wasted time, which means if I'm driving an Uber I don't get paid. There also is a difference between permanent venues, like a football stadium, which have the same problems every weekend (while football isn't being played these stadiums are often used for other things, like concerts) and music festivals that only happen one or two weekends a year, like Coachella. There aren't enough vehicles to support these temporary crowds so vehicles have to be moved into that area. There are dozens of such festivals all over the world, and that's counting just the ones with 50,000 attendees or more, like EDC in Vegas, Glastonbury in UK, etc. So, a company, like a Tesla, which is expected to have humanless vehicles driving in most Western Countries, would need to work with dozens of venues to setup drop off and pick up zones, and with local police to understand how to work with them so that they understand how to work with autonomous vehicles. Once in a while one of those will get stuck, for instance, maybe with a blown tire or an equipment malfunction, or, worse, an accident. At SXSW a drunk driver plowed through crowds of people one year, killing many, and causing a major first-responder response. In such a situation all the constituencies would need to work together to change traffic flows to make sure more vehicles aren't drawn to the area, or interfere with first responders. Is there a relationship lead between all these constituencies? I hear there is not, except in the best of cases. So, this leads to a new job for humans. AI's can't attend city council or meetings with police. AI's can't often figure out why all traffic has stopped. Once, at Half Moon Bay's pumpkin festival it started to rain. Everyone headed for their cars at the same time, but both Waze and Apple Maps continued to give incorrect data for an hour, both on recommendations for what street to head down, and on time it will take to get out of the area. These systems are built for normal traffic flows, and often can't understand that police have even reversed traffic, so that cars are going down the wrong way on a road. Which leads to the AI. Uber's founder, Travis Kalanick, told me his goal is to have one car near someone who is calling for a ride. That way the ride will arrive in less than five minutes and everyone is happy. Uber built a complex "traffic control system" that hooks drivers and passengers up together. That system usually works great, but when high-crowd events show up these systems often mislead drivers and passengers alike. Waymo is, so far, punting, and refuses to go near these events, and has a very small number of passengers today. Even if you live in San Francisco you can't just get a Waymo, you have to wait to be added to the system and they are adding new passengers slowly so that the whole system remains healthy and doesn't hit these large-crowd issues yet. That will change as they scale up the system to be in many more cities over the next few years and open up the system to everyone, not just a limited number of beta testers. So, to wrap it up, soon entrepreneurs, like Elon Musk, who is making plans for bringing its millions of vehicles online to do human-less driving, will need to do new AI modeling work for how cars should behave around high-crowd events, leading to new traffic-control systems to bring thousands of cars in and out of these venues, and will need teams of humans working with venues and cities to build new drop-off-areas for autonomous vehicles to drop off and pick up people. That is a human job, not one that an AI or robot can do. And a company that has aspirations for building a global network of autonomous vehicles, will need many such workers to work with local customs/officials/venues/teams/events. I see very little modeling work, although I saw MIT Media Lab doing some early work to understand how cities would change due to autonomous vehicles, and I don't see anyone in the AI/Autonomous Vehicle industry talking about research/work in this areas. (And yes, I do have a list of those people here on X: https://x.com/scobleizer/lists) I'm doing this post to try to spur industry interest in working on these issues and to connect people who may already be working on them. Are you positioned for these new jobs? If you are, these are fun things to work on and you might even get free tickets to go see concerts or football games for you and your family. I got taken to a Taylor Swift concert by an entrepreneur who built technology systems for the local stadium, so I know it's possible. :-) Technology solves old problems and causes new problems. Which is why I'm still on team human. AI's aren't good at figuring this stuff out and I don't see them getting good at figuring them out, either, for years. Sounds like a good job to have for a while. Here's a new problem, and a new set of jobs for humans, that will be caused as more and more Robotaxis show up (think of an Uber that works without a human in the car). What is the problem? Transportation behavior will change as we get more and more vehicles on the road with no humans inside. Something that's already happening in San Francisco, where you see many autonomous vehicles driving around with no humans inside from companies like Waymo, Zoox, and others. Expected are many others, including Tesla, and GM's Cruise which we hear will be back on the road later this year. The problem? Football stadiums, concerts, basketball stadiums, conferences, events like the Olympics, all will see radically different usage patterns. For instance, today, if you attend a football game, you park in one of dozens of parking lots around the stadium and you walk in, or take a shuttle to one of the entrances. This adds some "randomness" to the flow of crowds in and out and lets city officials who plan out traffic flows bring traffic to those parking lots with a few different routes. Even today it's often a mess with traffic taking an hour to get into many venues with large numbers of people but officials, and others, who work in these industries tell me autonomous vehicles will make traffic far worse. Why? Well, let's assume in five years you are in a Cybertruck taking your family to a football game and that by then the Cybertruck can drive with no humans in the car. Will you want your Cybertruck to take you to a far off parking lot and make you walk to the stadium? No. You'll want it to drop you off near the football stadium. And here's the rub: so will everyone else. Which means you'll have thousands of Waymos, Cruises, Teslas, all trying to get to the same drop-off point. This new human expectation will lead to traffic nightmares. Worse, I've been talking with executives at these kinds of venues and they say the coordination between sports teams, city officials/police, and ride-sharing companies is nearly non-existent.One told me they tried to get Uber and Lyft to come meet with them to design new traffic flows for their vehicles and they just don't get very little help or interest from the ride-sharing companies. One, who works with the 49ers, tells me city officials often put up signs for Uber/Lyft drivers that lead them into dead-end roads where they need to waste time turning around and figuring out where they need to go. Signage, cones, road closures, all could be done in a much better way around venues. And that's before you consider the humans. Often crowds of humans getting out of venues are drunk, don't follow traffic rules, and, sometimes, even turn riotous. Has the autonomous vehicle industry worked with venues to understand how traffic systems change around event venues? No, is the answer I keep hearing, and getting Waymo or Tesla interested in studying the problem together and designing new traffic facilities around big-crowd venues is difficult. Oh, it can happen. At Coachella, for instance, Uber built a huge parking lot with waiting areas for humans that were covered (it's hot often waiting for your ride to show up). Uber also built contextual systems to work with drivers around the Western United States to convince drivers to come to Palm Springs for a month and drive people around (Coachella is two weekends, where 150,000 people visit each weekend, followed by a country music festival that has slightly smaller crowds, but Uber, alone, brings thousands of cars to handle the crowds of people who want to use it to get to and from the venue). Along with the parking lot city officials block off lanes and have clear signs for Uber/Lyft/Taxis to use and have police at every intersection directing traffic and making sure things flow smoothly. Even with all that work it often takes one to three hours of standing in line to get a Taxi or an Uber out of the venue. Now imagine if thousands of people were arriving in autonomous vehicles. If the vehicles weren't programmed into where to go, and if Tesla doesn't have its own drop off and pickup lot things could get nasty, and fast. Last week at NVIDIA's big event my Tesla was programmed to pick up a friend at the Marriott. Problem was it took me down a route that is usually just fine, but during that event NVIDIA and city officials had the street in front of the conference center closed due to the large crowds that were attending that event. My Tesla didn't know about the closed street so it tried to take me down that closed street, figured it out too late, and then got stuck in traffic going on a detour around, wasting 15 minutes. Now 15 minutes doesn't seem like a big deal, but it is if I was driving an Uber passenger. Why? Well, first of all now I have a passenger who isn't happy with the navigation choices the car made, maybe giving me a lower score than I otherwise would get, but, worse, if I was picking up a passenger that person might see that I'm now 15 minutes away instead of two and decide to hop in a cab or cancel my ride. Wasted time, which means if I'm driving an Uber I don't get paid. There also is a difference between permanent venues, like a football stadium, which have the same problems every weekend (while football isn't being played these stadiums are often used for other things, like concerts) and music festivals that only happen one or two weekends a year, like Coachella. There aren't enough vehicles to support these temporary crowds so vehicles have to be moved into that area. There are dozens of such festivals all over the world, and that's counting just the ones with 50,000 attendees or more, like EDC in Vegas, Glastonbury in UK, etc. So, a company, like a Tesla, which is expected to have humanless vehicles driving in most Western Countries, would need to work with dozens of venues to setup drop off and pick up zones, and with local police to understand how to work with them so that they understand how to work with autonomous vehicles. Once in a while one of those will get stuck, for instance, maybe with a blown tire or an equipment malfunction, or, worse, an accident. At SXSW a drunk driver plowed through crowds of people one year, killing many, and causing a major first-responder response. In such a situation all the constituencies would need to work together to change traffic flows to make sure more vehicles aren't drawn to the area, or interfere with first responders. Is there a relationship lead between all these constituencies? I hear there is not, except in the best of cases. So, this leads to a new job for humans. AI's can't attend city council or meetings with police. AI's can't often figure out why all traffic has stopped. Once, at Half Moon Bay's pumpkin festival it started to rain. Everyone headed for their cars at the same time, but both Waze and Apple Maps continued to give incorrect data for an hour, both on recommendations for what street to head down, and on time it will take to get out of the area. These systems are built for normal traffic flows, and often can't understand that police have even reversed traffic, so that cars are going down the wrong way on a road. Which leads to the AI. Uber's founder, Travis Kalanick, told me his goal is to have one car near someone who is calling for a ride. That way the ride will arrive in less than five minutes and everyone is happy. Uber built a complex "traffic control system" that hooks drivers and passengers up together. That system usually works great, but when high-crowd events show up these systems often mislead drivers and passengers alike. Waymo is, so far, punting, and refuses to go near these events, and has a very small number of passengers today. Even if you live in San Francisco you can't just get a Waymo, you have to wait to be added to the system and they are adding new passengers slowly so that the whole system remains healthy and doesn't hit these large-crowd issues yet. That will change as they scale up the system to be in many more cities over the next few years and open up the system to everyone, not just a limited number of beta testers. So, to wrap it up, soon entrepreneurs, like Elon Musk, who is making plans for bringing its millions of vehicles online to do human-less driving, will need to do new AI modeling work for how cars should behave around high-crowd events, leading to new traffic-control systems to bring thousands of cars in and out of these venues, and will need teams of humans working with venues and cities to build new drop-off-areas for autonomous vehicles to drop off and pick up people. That is a human job, not one that an AI or robot can do. And a company that has aspirations for building a global network of autonomous vehicles, will need many such workers to work with local customs/officials/venues/teams/events. I see very little modeling work, although I saw MIT Media Lab doing some early work to understand how cities would change due to autonomous vehicles, and I don't see anyone in the AI/Autonomous Vehicle industry talking about research/work in this areas. (And yes, I do have a list of those people here on X: https://x.com/scobleizer/lists ) https://x.com/scobleizer/lists I'm doing this post to try to spur industry interest in working on these issues and to connect people who may already be working on them. Are you positioned for these new jobs? If you are, these are fun things to work on and you might even get free tickets to go see concerts or football games for you and your family. I got taken to a Taylor Swift concert by an entrepreneur who built technology systems for the local stadium, so I know it's possible. :-) Technology solves old problems and causes new problems. Which is why I'm still on team human. AI's aren't good at figuring this stuff out and I don't see them getting good at figuring them out, either, for years. Sounds like a good job to have for a while.

On The Drop Off and Pick Up Problem for Robotaxis at Crowded Events like Football Games and Concerts

ফুটবল গেমস এবং কনসার্টের মতো ভিড়পূর্ণ ইভেন্টগুলিতে রোবোটক্সির জন্য ড্রপ অফ এবং পিক আপ সমস্যা

Zum Bring- und Abholproblem für Robotertaxis bei überfüllten Veranstaltungen wie Fußballspielen und Konzerten

Πρόβλημα κατά την παράδοση και την παραλαβή για ρομποταξία σε πολυσύχναστες εκδηλώσεις όπως αγώνες ποδοσφαίρου και συναυλίες

Sobre el problema de dejar y recoger a los robotaxis en eventos multitudinarios como partidos de fútbol y conciertos

Բազմամարդ իրադարձությունների ժամանակ, ինչպիսիք են ֆուտբոլային խաղերը և համերգները, ռոբոտաշինգի խնդիրը թողնելու և վերցնելու մասին

Sul problema del ritiro e della consegna dei robotaxi durante eventi affollati come partite di calcio e concerti

サッカーの試合やコンサートなどの混雑したイベントでのロボタクシーの降車・乗車問題について

Robotaxis izlaišanas un uzņemšanas problēma pārpildītos pasākumos, piemēram, futbola spēlēs un koncertos

Problemă de livrare și ridicare pentru Robotaxis la evenimente aglomerate precum jocuri de fotbal și concerte

Dejinta oo u soo qaado dhibta Robotaxis ee Munaasabadaha dadka badan sida Ciyaaraha Kubadda Cagta iyo Riwaayadaha

Kwenye Kuacha na Kuchukua Tatizo kwa Roboteksi kwenye Matukio yenye Watu wengi kama vile Michezo ya Kandanda na Tamasha

Eka The Drop Off and Pick Up Problem for Robotaxis eka Swiendlakalo leswi Taleke ku fana na Mintlangu ya Bolo ya Milenge na Tikhonsati

124 Stories To Learn About Youtube

383 Stories To Learn About Career Advice

Let's learn about via these 79 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Youtubers /Learn Repo 1. The State of AI in 2022: An End-of-Year Recap of the Machine Learning Industry An 8-minute AI rewind with results and limitations of all the hottest AI models shared in 2022! 2. An Interview with Quadruple Kaggle Grandmaster Chris Deotte from NVIDIA In this episode, I interview Chris Deotte, one of the very few Kaggle quadruple grandmasters. 3. How to Enable Autocomplete (and AI) in your Terminal Here's how I enhance my terminal with autocomplete and Artificial Intelligence 4. GPT-4 Explained: ChatGPT's Big Brother is Here to Disrupt Everything If you thought ChatGPT was good, just wait until you try GPT-4. 5. 5 Docker Desktop Alternatives For Windows and macOS users, Docker Desktop has been the main way to use Docker containers for many years. But how about now? 6. #FoundersConnect: Interview with Hanu Agbodje, the Founder and the CEO of Patricia In this episode, Peace Itimi interviews Hanu Agbodje, CEO of Patricia, on his journey as a tech entrepreneur and 7. Making the Case for Why React Native is Garbage Ex-Google/ex-Facebook TechLead presents the case against the React Native cross-platform mobile app framework.  Join my interview training prep here http://techinterviewpro.com/ 8. 8 BEST Crypto Wallets for Beginners If there’s one thing that every crypto investor needs to have, it’s a crypto wallet. There are all kinds of different crypto wallets you can use. 9. The New AI Model Lets You Generate Music via Text Prompt We recently covered a model able to imitate someone’s voice called VALL-E. Let’s jump a step further in the creative direction with this new AI called MusicLM. MusicLM allows you to generate music from a text description. 10. 6 Common Monetization Problems for Creators on YouTube If you are a video creator looking for ways to make your videos work hard, you are not wrong in worrying about Youtube monetization issues. Read on to know the how-tos and what-nots of monetizing your videos. 11. Top 10 Computer Vision Papers of 2020 This is a video of the 10 most interesting research papers on computer vision in 2020. 12. Google's PaLM-E (AI Robot) Can See and Understand Language Google's latest publication, PaLM-E, is an embodied multimodal language model. 13. OBS for Dummies : How to Record Your Screen Wait... OBS..I have heard it somewhere. 14. Top 8 Machine Learning Content Creators on YouTube Here are the top Machine Learning content creators on YouTube to follow for tutorials, deep learning, and more. 15. 'Why I don't eat out at restaurants, even as a millionaire' - TechLead Ex-Google Tech Lead reveals the secret to why he doesn't enjoy eating out at restaurants, even as a multi-millionaire. 16. How to Get Started Streaming on Twitch Twitch is a great place to learn in public. I'll cover tools, tips, and workflows to help you get started with streaming. 17. How to Turn Mockups Into Videos Instantly with This New AI Model GEN-1 is able to take a video and apply a completely different style onto it, just like that… 18. 5 Gaming YouTubers That are Worth a Sub There are far too many people sharing their opinions about gaming on the internet but not all of them are for us. These are some people who we enjoy the most. 19. Even Disney is Investing in AI: A Look at Face Re-Aging for Visual Effects Whether it be for fun in a Snapchat filter, for a movie, or even to remove a few riddles, we all have a utility in mind for being able to change our age in a picture. 20. 6 Vlogging Tips For Business Success in 2020 Vlogging has taken the world by storm in recent years. It's just a way of blogging, using videos instead of text to reach out, create an audience, and share information. 21. 5 Gaming YouTubers That are Worth a Sub There are far too many people sharing their opinions about gaming on the internet but not all of them are for us. These are some people who we enjoy the most. 22. Youtube Deletes Video About Bitcoin: Is This a Common Trend? You would think that Youtube would at least wait till the holidays are over to hit its creators with this news but apparently, bitcoin and all cryptocurrency talk is now concrete himself and a danger to society. A lot of YouTube creators woke up to find many of their crypto-related videos taken down because youtube sees them as violating their guidelines. 23. How to Use GitHub Copilot with Your Voice “Hey, GitHub” comes in the form of a VSCode extension and has many more capabilities accessible with your voice. 24. How to Ace ML Interviews: Get Your Foot in the AI Door An interview with the Director of Perception at Zoox, Ruijie (RJ) He, with the goal of demystifying what is a good profile to get an ML engineer job and perform 25. 3D Articulated Shape Reconstruction from Videos With LASR, you can generate 3D models of humans or animals moving using only a short video as input. 26. How to Set Up Aleph.im Virtual Machines Nearing the end of 2021, most blockchain dApps still have large parts of their stack that are centralized. With Aleph VMs, you can decentralize the rest. 27. Let’s Play Ethermore: Part 1 – Exploring The Ruins of Nio Cegod Ethermore's first-ever let’s play video is being used to showcase a possible new feature: AI-generated synthetic audio narration. 28. 5 Ways to Get More Likes on Your YouTube Videos Business owners and marketers around the globe know that YouTube is one of the best places to connect with their target audience. 29. The Facebook TransCoder Explained: Converting Coding Languages with AI This new model converts code from a programming language to another without any supervision! 30. The Best AI Articles of October 2022 Support vector machines, decision trees, and AI-generated content are some of the topics in the best AI articles of October. 31. ChatGPT Explained in 5 Minutes ChatGPT has taken over Twitter and pretty much the whole internet, thanks to its power and the meme potential it provides. 32. 5 Strategies To Grow Your YouTube Channel YouTube is the most popular online video platform as of now. Over hundreds of hours of content is uploaded every minute on this platform, and on average, the viewership crosses billions of hours every day. 33. YouTube Fake Crypto Giveaways Explained - Behind The Account Hacks Maybe you have noticed that there is a lot of fake Binance, Ethereum, Ripple and Bitcoin Cash streams on Youtube lately. The crazy part is that those live streams are on a big accounts with thousands of subscribers. 34. 8 Tools Every Data Scientists Should Use The most useful tools I use daily as a research scientist for finding and reading AI research papers 35. OpenAI's New Code Generator: GitHub Copilot (and Codex) You’ve probably heard of the recent Copilot tool by GitHub, which generates code for you. Find out how OpenAI's AI generates code from words 36. Introducing DALL·E: Inspired by GPT-3 and Image-GPT from OpenAI DALL-E from Open AI can generate images from text captions. It is very similar to GPT-3 and Image GPT and produces amazing results. 37. How to Optimize a YouTube Channel: 15 Effective Tips Competing on YouTube isn’t an easy task. Here are 15 effective ways to optimize your channel. Follow these ways to optimize now. 38. PSG is a New Task for AIs Requiring Higher Levels of Understanding Panoptic scene graph generation, or PSG, is a new problem task aiming to generate a more comprehensive graph representation of an image or scene based on panoptic segmentation rather than bounding boxes. It can be used to understand images and generate sentences describing what's happening. This may be the most challenging task for an AI! Learn more in the video... 39. Will Transformers Replace CNNs in Computer Vision? This video explains how transformer architecture can be applied to computer vision with a new paper called the Swin Transformer. 40. Galactica is an AI Model Trained on 120 Billion Parameters On November 15th, MetaAI and Papers with Code announced the release of Galactica, a game-changer, open-source large language model trained on scientific knowledge with 120 billion parameters. 41. DALL·E 2 Pre-Training Mitigations You’ve all seen amazing-looking images like these, entirely generated by an artificial intelligence model. I covered multiple approaches on my channel, like Craiyon, Imagen, and the most well-known, Dall-e 2.Most people want to try them and generate images from random prompts, but the majority of these models aren’t open-source, which means we, regular people like us, cannot use them freely. Why? This is what we will dive into in this video... 42. This AI Can Separate Speech, Music and Sound Effects from Movie Soundtracks Have you ever tuned in to a video or a TV show and the actors were completely inaudible, or the music was way too loud? Well, this problem, also called the cocktail party problem, may never happen again. Mitsubishi and Indiana University just published a new model as well as a new dataset tackling this task of identifying the right soundtrack. For example, if we take the same audio clip we just ran with the music way too loud, you can simply turn up or down the audio track you want to give more importance to the speech than the music. 43. Meta's Groundbreaking AI Film Maker: Make-A-Scene Meta AI’s new model make-a-video is out and in a single sentence: it generates videos from text. It’s not only able to generate videos, but it’s also the new state-of-the-art method, producing higher quality and more coherent videos than ever before! 44. How YouTubers Can Improve Their Marketing Strategies in 2021 2020 with its lockdown affected both video creation and consumption, and that resulted in new rules in video marketing. 45. How to Spot a DeepFake in 2021 How to Spot a Deep Fake in 2021. Breakthrough US Army technology using artificial intelligence to find deepfakes. 46. What is the InfiniteNature-Zero AI Model? This AI generates infinite new frames as if you would be flying into your image! 47. Efficient NeRFs for Real-Time Portrait Synthesis (RAD-NeRF) We’ve heard of deepfakes, we’ve heard of NeRFs, and we’ve seen these kinds of applications allowing you to recreate someone’s face and pretty much make him say whatever you want. 48. DeOldify can Colorize your Black & White Photos with Full Photorealistic Renders DeOldify is a technique to colorize and restore old black and white images or even film footage. It was developed by Jason Antic. 49. OpenAI’s DALL·E: Text-to-Image Generation Explained OpenAI just released the paper explaining how DALL-E works! It is called "Zero-Shot Text-to-Image Generation". 50. How to Talk to ChatGPT: An Intro to Prompt Engineering Prompting is pretty much the only skill you now require to be a master of these new large and powerful generative models such as ChatGPT. 51. This AI Prevents Bad Hair Days This AI can transfer your hair to see how it would look like before committing to the change. 52. VOGUE by Google, MIT, and UW: The AI-Powered Online Fitting Room Google used a modified StyleGAN2 architecture to create an online fitting room where you can automatically try-on any pants or shirts you want using only an ima 53. How Uber Uses AI to Improve Deliveries How can Uber deliver food and always arrive on time or a few minutes before? How do they match riders to drivers so that you can find a Uber? All that while also managing all the drivers?! always 54. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 55. Text Embedding Explained: How AI Understands Words Large language models are a specific type of machine learning-based algorithm that understand and can generate language 56. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 57. How Apple Recognizes People in Private Photos via Machine Learning Apple uses machine learning to directly recognize people in private photos on your iPhones and iPad, without having access to your images for training. 58. Is Subjective Beauty Something We Can Model with AI? This AI reads your brain to generate personally attractive faces. It generates images containing optimal values for personal attractive features. 59. Using AI to Detect and Count Plastic Waste in the Ocean A deep-learning-based algorithm that is able to detect and quantify floating garbage from aerial images of the ocean. 60. Imagic: AI Image Editing from Text Commands This week’s paper may just be your next favorite model to date. 61. Google Brain's New Model Imagen is Even More Impressive than Dall-E 2 If you thought Dall-e 2 had great results, wait until you see what this new model from Google Brain can do. Dalle-e is amazing but often lacks realism, and this is what the team attacked with this new model called Imagen. They share a lot of results on their project page as well as a benchmark, which they introduced for comparing text-to-image models, where they clearly outperform Dall-E 2, and previous image generation approaches. Learn more in the video... 62. Combining CNNs, GANs, and Transformers to Outperform Image-GPT Researchers combined the efficiency of GANs and convolutional approaches with the expressivity of transformers to outperform Open AI's Image-GPT 63. Introducing Total Relighting by Google In a new paper titled Total Relighting, a research team at Google presents a novel per-pixel lighting representation in a deep learning framework. 64. What is Data Science like at NVIDIA? What is it like to work in big companies like NVIDIA, and how to get there? 65. How to Create Realistic Slow Motion Videos With AI TimeLens can understand the movement of the particles in-between the frames of a video to reconstruct what really happened at a speed even our eyes cannot see. 66. What is OpenAI's Whisper Model? Have you ever dreamed of a good transcription tool that would accurately understand what you say and write it down? Not like the automatic YouTube translation tools… I mean, they are good but far from perfect. Just try it out and turn the feature on for the video, and you’ll see what I’m talking about. 67. An Intro to eDiffi: NVIDIA's New SOTA Image Synthesis Model eDiffi, NVIDIA's most recent model, generates better-looking and more accurate images than all previous approaches like DALLE 2 or Stable Diffusion. 68. How Waymo Combines Lidar and Cameras for 3D Object Detection Let us talk about how autonomous vehicles 'see' the world. 69. NVIDIA and Tel Aviv University's Approach to Conditioning Text-to-Image Models Text-to-Image models like DALLE or stable diffusion are really cool and allow us to generate fantastic pictures with a simple text input. But would it be even cooler to give them a picture of you and ask it to turn it into a painting? Imagine being able to send any picture of an object, person, or even your cat, and ask the model to transform it into another style like turning yourself into a cyborg of into your preferred artistic style or adding it to a new scene. 70. New SOTA Image Captioning: ClipCap We’ve seen AI generate images from other images using GANs. Then, there were models able to generate questionable images using text. In early 2021, DALL-E was published, beating all previous attempts to generate images from text input using CLIP, a model that links images with text as a guide. A very similar task called image captioning may sound really simple but is, in fact, just as complex. It is the ability of a machine to generate a natural description of an image. 71. Secrets to Grow a Small Business Without Spending Money Ex-Google Tech Lead shares his experience in growing a business from 0 to millions of users fast, and his top tips for you to get going too. 72. What is General Video Recognition? We’ve seen AI generate text, then generate images and most recently even generate short videos 73. Would You Swipe Right for an AI Profile? Most of us are convinced that we can dissociate humans from machines, but is it really the case?  Would you swipe right for an AI-generated profile? 74. Convolutional Neural Networks (CNNs) Explained What is a convolutional neural network and explanation of one of the best and most used state-of-the-art CNN architecture in 2020: DenseNet. 75. How to Make $40K Per Month in Your 20's: Building a Side-Business Ex-Google Tech Lead talks about building a side-hustle and making $40K/month in your 20's. 76. Top 5 AI Articles of February 2022 Every Data Scientist Should Read Here are the five best articles related to artificial intelligence in February, hoping they will make you want to learn more and visit their website. 77. How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML How to start machine learning & Ways to keep up with the latest developments in Machine Learning. 78. How to Get Started With AI in 2021 and Keep Up with Latest Innovations in ML How to start machine learning & Ways to keep up with the latest developments in Machine Learning. 79. 'How I got a $500K job at Facebook (as a software engineer)' - TechLead Ex-Google TechLead explains the interview process at Facebook for staff software engineer.  (FYI, this video is a little more technical in nature.) Thank you for checking out the 79 most read stories about Youtubers on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

79 Stories To Learn About Youtubers

341 Stories To Learn About Tech Careers

HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of the Year” award, featuring the most promising and innovative companies in the San Diego startup ecosystem. San Diego, CA - May 24, 2023 - https://www.youtube.com/watch?v=ZqIW54yMsNc&embedable=true The list, compiled by the HackerNoon team, showcases that are making significant contributions to the San Diego economy and driving innovation in their respective industries. 133 startups The nominated for Startups of the Year 2023 include: Startups in San Diego GoFormz Lively Root Platform Science Kahoona Tag-N-Trac Launch Factory comma Zoox Streamlined Robin Healthcare KÉXY ChargeNet Stations Replay RobustPhysics Sensorydata Skillmasters.io Truepic Blueboard 6Storage XRA Lawmatics Brain Doctible Classy.org Helix GoShare Sportidia The Good Face Project Cloudbeds ClickUp You can nominate your company as the . startup of the year in San Diego here “We are thrilled to recognize the top startups in San Diego and celebrate their achievements,” said . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO is a community-driven voting platform that recognizes startups that are changing technology and the world for the better. Starting May 8th, 2023, the internet can nominate and vote for the best ventures in their city. The voting period will remain open until December 31, 2023, and winners will be announced in January 2024 after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 In its , a total of 44,427 startups were nominated in 16 different regions, and the community cast 234,344 votes during a 6-month long campaign in favor of budding companies that were growing and trending across every major city in the world. The received perks from sponsors and a free from HackerNoon. previous iteration 1,382 winners tech company news page As a proponent of the open data movement, HackerNoon releases the unique social data gathered from Startups of the Year on GitHub as “ ” for valuable insights. /where-startups-trend Apart from validation from the world's greenest tech publication, all nominees relevant to their domain, region, and funding. They will also receive an and a free version of their very own on HackerNoon. get free interviews amazing discount package designed for their startup Tech Company News Page These pages include business overviews (such as head count, founding year, bio, social links, and domain ranking) coupled with dynamic updates every time the company is mentioned in HackerNoon stories or relevant headlines around the web. People can , and vote once per day per award for who they think should be Startup of the Year all the way up to December 31st. nominate their favorite startups until June 8th In addition to the award itself, winners receive exclusive interviews, an exclusive NFT from HackerNoon, and a .Tech Domain for life. For more information about the “Startups of the Year 2023” list and the nominated companies, please visit our . FAQ page About HackerNoon HackerNoon is a technology publication that aims to empower developers, entrepreneurs, and tech enthusiasts to share their knowledge and expertise with a global audience. With millions of monthly readers, over 500,000 followers on social media, and over 250,000 newsletter subscribers, HackerNoon provides a platform for startups and innovators to showcase their work and connect with a vibrant community of like-minded individuals. Did you know that companies that actively engage in blogging experience a whopping 67% increase in leads? Take advantage of HackerNoon's ' ' to kickstart your own company's blogging journey. Startups Package Startups Of The Year 2023 is sponsored by . .Tech Domains You can nominate your company as the . startup of the year in San Diego here

Startups of The Year 2023: 130+ Startups Nominated in San Diego

Here's an interview with the Director of Perception at Zoox, Ruijie (RJ) He, with the goal of demystifying what a good profile is to get an ML engineer job and perform well at the interviews. We go over many points from the current job market, the screening process, how to prepare for an interview, the interview process and the role of an ML engineer at Zoox. For an introduction, Zoox is an artificial intelligence company focused on a single product: autonomous vehicles. They are building intelligent taxis for the future hiring a lot of people in the whole machine learning / data science space. Let's learn about the type of people they are keen to hire... Watch the interview: Let me know who you would like me to interview next or the topic you'd like to learn more about!

How to Ace ML Interviews: Get Your Foot in the AI Door

In February 2022, I finally moved to the US on O1 work visa. This was preceded by 2.5 years of work on strengthening the case, waiting for approval. 1.5 years before this date, I started preparing for an interview for a Front End position. Currently working as a Senior Front-End Engineer at Roku. This post and the creation of the were motivated by the lack of detailed information about interviews for Front-End engineers in the USA. telegram channel What I did before Before relocation, I worked for 7 years in outsourcing companies in Belarus. This allowed me to use different technologies, approaches and work on various projects. Prior to relocating, I already held a position as Engineering Manager with 26 JavaScript engineers (this strengthened my CV, especially for a Staff position). Over the past year, I have conducted about 50 technical interviews in the department. But in the USA, I realized that my experience is not entirely relevant, and I need to start from a Senior position in order to figure out how the processes are built here, the culture, and how to conduct interviews, which are completely different here. I started preparing for the technical interview 1.5 years in advance while I was waiting for my visa. Every morning of my working week was spent for preparing. It became a habit over time and did not cause any discomfort. After a while, I was promoted to the Engineering Manager position as I was growing at a rapid rate. Preparation 1. Leetcode I solved 245 problems on leetcode. I mostly focused on arrays, matrix, trees, linked lists, strings, hash tables, sorts, and two pointers. In my , you can see the topics that I solved. profile are all the tasks that I solved. Here To familiarize and refresh data structures and algorithms in JS, I used the resource. javascript-algorithms To quickly identify a Leetcode problems patterns, read this article — . It helps identify the problem. 14 Leetcode problems patterns To determine the complexity of the code, there is a on Big O notation. cheat sheet For examples of ​​what an interview looks like, I used the resource. interviewing 2. Big Front End ( ) https://bigfrontend.dev/ I solved 50% of BFE problems (easy and medium). I published all these solutions on my t . This resource is most useful for interviews at Meta, but other companies are more or less likely to ask similar questions. elegram channel 3. System design To prepare for system design, I used videos. He covered most aspects of systems design that I encountered in real interviews. Evgenii Ray’s A very useful resource for system design and for real work (Web Performance) — 3perf All about accessibility 4. Behavioral interview for preparation and examples of answers. List of questions For the mock interview, I used the telegram channel and . FAANG Pramp I also used this and and resolved everything from there, reading it all the way through. telegram channel Evgenii Ray’s Notion On glassdoor, you can find some examples of questions and tasks that companies ask. And finally, I’m in the USA… Upon arrival, I had a 2-week jet lag, there was no way of passing the interview, I could not sleep normally. But after I adapted, I began to actively set up calls with recruiters, writing on LinkedIn. There were 20–30 messages with opportunities per day, but most of them are no-name companies or startups. Before replying to the message, I analyzed the company, investments, it is a public or private company, what they do and what technologies they work with (I basically focused on React.js, JS / TS stack, as well, the Front End position). This was the original filter. During the day I had 3–4 phone calls with recruiters, then 2 technical interviews. In total, I participated in about 20 mocks to understand how to behave in an interview and what my weaknesses are, but this does not compare with real interviews. In real interviews, I already had a noticeable growth, already after 1–1.5 months, I began to solve problems more efficiently, find out requirements, sell myself and answer behavioral questions, because after each interview I did work on mistakes, and corrected stories. I started with small startups and companies and I was ready for rejection (this is important!). Every day for 2 months I had phone calls with recruiters, technical screenings, on-site interviews. It is very convenient that now everything is online. After almost a month of technical screenings, I even said that I liked the interview process, there are so many interesting problems and people, but then the onsite time came … after the first 5-hour interview, my opinion changed in a completely different direction, it’s sooo hard! In the beginning, I had rejections and it was frustrating of course. But as soon as I received the first offer, my motivation immediately grows .. until the next rejection. I was ready for rejection, but it’s still unpleasant to hear, especially when you spent 5–6 hours and they send you a standard reply that we decided to move with another candidate without any feedback. This motivated me to reflect and analyze what went wrong. I took notes, and tried to find answers on how to solve the problem or what needed to be clarified and how to design something. This helped in future interviews to combine different solutions into one and produce a high-quality solution. Also, communication with recruiters helped me improve my English, at the beginning I might not even understand half of what they were saying to me, but then I got used to it and it was much easier. In the end, I had really good interviews, but I kept getting rejected for some of them. And the worst thing is, you don’t understand what went wrong. The interview process My interview stats: : Meta, Amazon, Apple, Google, Microsoft, Lyft, Uber, LinkedIn, Roku, Salesforce, PayPal, DoorDash, Robinhood, Roblox, Intuit, Zoom, Grammarly, Imply, Disco, Square, SigmaComputing, LiveRamp, Zoox, Palo Alto Networks, Snowflake, Aurora Tech Screens (26) : Meta, Amazon, Google, Microsoft, LinkedIn, Roku, Salesforce, PayPal, DoorDash, Zoom, Grammarly, SigmaComputing, LiveRamp, Zoox, Aurora Onsite interviews (15) : Google, Roku, Microsoft, PayPal, SigmaComputing, LiveRamp Offers When applying for a Front End position, you will likely be asked only questions about the frontend, but at least 1 algo-problem of the easy-mid level will be asked, mainly about the data structure and its processing (there are not a lot in JS :)). But some like to ask algorithms the old-fashioned way. All of the preparation materials I mentioned above covered the interview questions. The process is pretty standard: Call with recruiter Technical screening Onsite (virtual) interview: Algorithms Tasks for coding a widget or a JS function System design, with a focus on Front-End Behavioral interview 4. Negotiation 1. Call with recruiter On a call with a recruiter, you discuss general questions, learn more about the company and the team you are interviewing. They ask about your work permit. In conversation, they ask about your experience and check your English. They find out what stage of your job search you are at and can build on this, for example, to speed up your interview process (In Aurora, I said that I completed all my interviews and if we can quickly go through all the stages, I agree. As a result, all the stages were done to me in 4 days, and onsite in just 3 rounds). Calls often happen before you have sent your CV. Only if everything went well and there is a match, you will be asked to send your CV. They may ask about your salary expectations, but I answered truthfully that I have no idea how much I am worth on the market since I just arrived. This was enough for them to pass over the question. You can ask for all the information you need in the same call, including the technical stack of the team. If you have questions that are important to you, this is the time to ask them. For me, it was the terms for the green card and the tech stack. Recruiters respect your time, so you coordinate each call according to the calendar, choosing from the recruiter’s one, or recruiter can choose from your calendar. Do not specify your salary expectations in any case, if they are very demanding (it has only happened once), specify a wide range. Turo’s recruiter repeatedly asked me what I expect, and when I gave him the range he said our compensation was 2 times less and we wouldn’t be able to match. 2. Technical screening So you have passed the first stage and you have been assigned a technical screening. Usually, it is 45 minutes. On it, again, you will tell a little about yourself, you will be asked questions about your experience and will be given to solve some small problem (in 90% it will either make a small widget in JS and a framework, or an easy problem for algorithms, or rather data structures that is in JS). Occasionally, there were problems on Hackerrank with HTML, CSS, and JS, 2–3. These are fairly simple to solve. Sometimes you can use any editor of your choice. But most of the time I send a link to my online editor (even with code highlighting). The most important thing is not to be silent, to think out loud so that the interviewer follows your thoughts. Related to code execution, it’s 50/50, sometimes you need to run the code when you want and as much as you want, sometimes I don’t even need to run the code (there’s not even such a possibility). There was one time when I was asked to design an elevator system at a technical screening (without code), it didn’t end well :) 3. Onsite(virtual) interview The most difficult stage of the interview, as it duration 3–6 hours. Many companies allow you to split it into 2 days, this is up to you. It consists of coding, system design, and behavioral interview. You can ask the recruiter about each round of onsite to understand what to expect from them. are similar to technical screening: find out the requirements, discuss the solution, code, and test it. Coding rounds System design Always focused on front-end issues, no need to talk about highly loaded systems, databases, etc. You just need to describe some functionality in the browser, ways to optimize, customize and expand, describe how to transfer data to the server, how to store it, where to store it, and why. Sometimes you need to design several endpoints with request and response structures. Don’t forget accessibility, it’s very important! Behavioral interview Here you can expect questions about your experience, projects, and teamwork. Basically, these questions are “Tell me a situation when you ..” In general, the questions asked about the most challenging project, the conflict in the team, what we did when deadlines were approaching and we didn’t have time, and what our biggest failure was. All stories should be told according to the STAR (situation — task — action — result) methodology. The story shouldn’t be very long. You will be asked clarifying questions if you didn’t explain something or the interviewer misunderstood you. In most cases, the hiring managers conduct the interviews. In the end, this is a great opportunity for you to ask all your questions about the team and the product. Negotiation There is no less stressful or important stage. It took me almost a month. With some companies, there were even several rounds, on average, I raised offers for 70–100k. Ask for feedback about you to better understand how good you were and use it as a negotiation tool. But nothing works better than a counteroffer. But it is important not to go too far, look at the compensations on the levels.fyi website beforehand in order to understand the range. Some conclusions about companies In all companies recruiters do a very good job and support you every step of the way, tell you what to expect in each round, how to prepare, and tell you what the interview process looks like in general. : I had the worst interview ever. At all rounds I had problems in understanding what the interviewer wanted from me, I clarified the requirements most of the time and explained my solution because for some reason they couldn’t understand it. And when they started asking questions about JavaScript during the coding process, it turned out that they didn’t know it and had to spend more time explaining why I use it and how it works. As a result, there were 5–7 minutes left for coding, but this was enough to finish. In the last round, I got the hard problem with trees, that I didn’t fully solve. Amazon : Some of the interviewers again didn’t know JavaScript, only asked algorithmic problems and asked questions about how JavaScript works. It was more like an interview for a full-stack position. Microsoft : Only math problems and algorithms were asked. Zoox : Again, only algorithms were asked, although the position is pure Front-End. However, my friend’s interview focused only on front-end questions. Aurora : I didn’t expect so much attention from this company. I had a lot of calls with a recruiter, the duration of some was an hour, where he told everything in detail about the interview process, gave preparation materials, asked how the preparation was going and gave advice, including how to behave in an interview, what to ask, what better not to ask. The questions were on the frontend focus. After the onsite, the hiring freeze started right away… Meta : They have an Ember.js framework, so questions are only about pure JavaScript and the frontend. LinkedIn : Lost my feedback after the technical screening. Still searching. Apple : The interview process was with front-end focus. After getting approval from the Google Hairing Committee, your next step is team matching. I had mixed feedback between L5 and L4 levels. As a result, the committee gave me L4 without additional interview stages. Only after a successful team match, they will send you an offer with numbers, but how long this process can take depends on many factors. Google I had 2 team calls a week, although I could do every day. The process took 2 weeks. The criteria by which I compared the teams: Team size. Frontend, backend, infrastructure engineers. Tech stack (all Angular). Promotion to L5 (time and opportunity). Product. Responsibilities. Front end or full stack position. There was even a backend only. Development process. Who are the users of the product, how many. Perhaps this is an internal project or a large one for a large number of users. Evaluated how comfortable communicate with the manager or team leader for me. As a result, I matched with the Google Analytics team, which is responsible for the performance of this product. In this team, I saw many opportunities for growth and metrics for promotion. How do I accept the offer I compared offers and decided which one to accept according to the following criteria. It is very important that the product is of interest to you. I have many years of experience in developing streaming platforms and know the needs of users and developers. I can learn a lot and see many challenges for myself in such products. Roku gives me this opportunity. Product. I don't like Angular, I prefer React.js. This was one of the most important reasons why I chose Roku. Tech stack and tools. This is a very important thing. I don't want to burn out. During the interview process, you can ask questions about it and listen carefully to the answers. Work-life balance. Growth in technical terms and within the company to the lead position (Staff) Opportunities for growth. After the position of engineering manager, I was not ready for middle positions (yes, there were those too). Position level. Base and stock. Roku pays 85% in cash for senior positions, which is more profitable for me, as a beginner in this country, since at this stage money is needed here and now. Total compensation. Some companies start the green card process from the 1st working day, some after 3, 6, 12 months. I filtered companies based on 1 day and 3 months. But as it turned out, these terms can also be negotiated, I was able to negotiate from 3 months to 1 working day.
An important nuance, Meta does not issue green cards, I asked them about it at every call, at every stage of the interview, but I never received an answer, no one at all. But according to information on the Internet, everything is bad with them. Green Card Process. I don't like working in a team where you are one Front End engineer, or even 2. I want to grow and learn. The level of engineers in the team was also important for me. Team size and responsibilities. I prefer office work. Working from home is not comfortable for me. Some companies now offer to work 3 days in the office, 2 days remotely, and some offer full remote work. Remote work or office work. I live in San Jose and some companies have offices in San Francisco. It will take you at least 1.5 hours to drive here. Do you want to spend 3 hours a day on this? Office location. Tips Do not schedule more than 3 (but preferably 2) onsites per week. Last week I had 4 onsites in a week and it was hell! But I got 2 offers :) In an interview, your skills grow exponentially, so do not immediately pass the interview with the company of your dreams. After the interview you can talk to someone, it helps to relax. Do work on the mistakes after each interview to understand what could have gone wrong, look for answers to questions and tasks that were in the interview and try to figure it out. Prepare the text for your self-presentation for 1–1.5 minutes, you will tell it at each stage of the interview. For a behavioral interview, prepare and practice as many STAR stories as you can, I had about 20 that covered almost all questions. It took about a month to prepare them. Buy a paid subscription to Calendly (or a similar service) to make it easier to manage your interviews. Sending the dates in an email means they can respond within a week, and demand 5 dates (respectively), so these 5 days are blocked for you and you cannot schedule other interviews on them. If you have any questions or topics that I have not covered, ask in the comments here or on my ! telegram channel

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