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Merge launches Blueprint, a tool that leverages OpenAI's GPT-3.5 LLM, allowing users to paste a link to the documentation of an API.

https://www.bing.com/th?id=OVFT.EiX3VbcH4t3QVGDpcFG_US&pid=News

Merge unveils Blueprint, an AI-powered tool to enable easier API integrations

https://www.bing.com/th?id=ODF.qPCJA3Or4GGU4hhi1ZEpfg&pid=news

VentureBeat

This strangely close embrace between AI doom and hype has at least one person at its center: Stability AI CEO Emad Mostaque.

https://www.bing.com/th?id=OVFT._RIkc2cBkZYFxpkZi0wlGS&pid=News

The thin line between AI doom and hype | The AI Beat

University of Virginia

Physics

Algorithm

Normally, when testing the behavior of materials under high heat or explosive conditions, researchers have to run simulation after simulation, a data-intensive process that can take days even on a supercomputer.

https://www.bing.com/th?id=OVFT.RjcVpqWMDoePG6naWYINTC&pid=News

UVA Researchers Built an AI Algorithm That Understands Physics

https://www.bing.com/th?id=ODF.6Lh6yqz2EK78-TVc-k6FcQ&pid=news

insidebigdata.com

The Matrix

Tata Group

India

Ahead of its possible foray into the semiconductor space, Tata Group is scouting land near its electronics manufacturing facility in Tamil Nadu to expand operations, sources told us. This and more in todays ETtech Morning Dispatch.

https://www.bing.com/th?id=OVFT.lO_Fhs364UR11-hruP5k6y&pid=News

Tatas eye bigger play in electronics, semicon manufacturing; Matrix closes largest India fund at $550 million

https://www.bing.com/th?id=ODF.OQKe7K2OTmm8-r2pCuWgdw&pid=news

Indiatimes

AndesAIRE™ AnDLA™ I350 is a deep learning accelerator (DLA) designed to enable high performance-efficient and cost-sensitive AI solutions for edge and end-point inference. It supports popular ... DMP's AI Processor IP, ZIA ™ DV 500, is the ultra low ...

Deep learning IP Listing

Design-Reuse

Exploring Machine Learning, AI, Deep Learning, Computer Vision - season - 1, Gradient Dissent: Exploring Machine Learning, AI, Deep Learning, Computer Vision - season - 1 Deploying Autonomous Mobile Robots with Jean Marc Alkazzi at idealworks, Lukas ...

Deploying Autonomous Mobile Robots with Jean Marc Alkazzi at idealworks

gaana

Brain

Decodes

They modified the loss function of an AI algorithm that performs contrastive learning so that it can use both discrete and continuous data streams. The new deep learning algorithm called CEBRA ...

AI Decodes Brain Activity to Predict What Mice See

Psychology Today

Edge computing

Real Time

Disease

A new study conducted by the University of California Santa Cruz (UC Santa Cruz) shows how an AI deep learning running ... of Electrical and Computer Engineering and the Narinder Singh Kapany ...

AI and Edge Computing Detect Disease for Real-Time Diagnosis

Alcatraz

Trulioo

“As we continue to develop immersive, AI-powered experiences, Iqbal’s extensive expertise in AI and deep learning, engineering, product development, and organizational leadership will be a vital asset. I am excited to see Iqbal’s contributions as we ...

Trulioo, Fourthline, SIA, Alcatraz expand boards

Biometric Companies

Deep learning has emerged as a revolutionary technology within the field of Artificial Intelligence (AI). At its core are neural networks, which have transformed the capabilities of AI systems.

Deep Learning: Unleashing the Power of Neural Networks in AI

LinkedIn

Uber Technologies, Inc. provides ride hailing services. The Company develops applications for road transportation, navigation, ride sharing, and payment processing solutions. Uber Technologies serves customers worldwide.

Uber Technologies, Inc. develops and operates proprietary technology applications in the United States, Canada, Latin America, Europe, the Middle East, Africa, and the Asia Pacific. It connects consumers with independent providers of ride services for ridesharing services; and connects riders and other consumers with restaurants, grocers, and other stores with delivery service providers for meal preparation, grocery, and other delivery services. The company operates through three segments: Mobility, Delivery, and Freight. The Mobility segment provides products that connect consumers with mobility drivers who provide rides in a range of vehicles, such as cars, auto rickshaws, motorbikes, minibuses, or taxis. It also offers financial partnerships, transit, and vehicle solutions offerings. The Delivery segment allows consumers to search for and discover local restaurants, order a meal, and either pick-up at the restaurant or have the meal delivered; and offers grocery, alcohol, and convenience store delivery, as well as select other goods. The Freight segment connects carriers with shippers on the company's platform and enable carriers upfront, transparent pricing, and the ability to book a shipment, as well as transportation management and other logistics services offerings. The company was formerly known as Ubercab, Inc. and changed its name to Uber Technologies, Inc. in February 2011. Uber Technologies, Inc. was founded in 2009 and is headquartered in San Francisco, California.

Uber

Why Is Uber Slow to Respond When Their Drivers Are Attacked?

This is by (source: ). Deedy is a founding engineer at Glean. Twitter thread Deedy @debarghya_das 02-18-2023 https://twitter.com/debarghya_das/status/1627136897914138625?s=46&t=KjebEkOH6bsGiEJC6yeS7w&embedable=true&thread=true Feature image generated via prompt of ‘Stock market in outer space’ HackerNoon Stable Diffusion

Uber's Stock Price Has Fallen Despite Increased Revenue

Uber released its Q4 2022 earnings report, revealing impressive growth in its core ride-hailing business with its “strongest quarter ever.” The company's Gross Bookings for the year reached $115 billion, an increase of 33% compared to last year's results. While total bookings in the mobility sector jumped to $14.9 billion from $11.3 billion, gross bookings in the delivery business increased to $14.3 billion from $13.4 billion in the December quarter, and Gross freight bookings increased 42% to $1.5 billion. The company reported a net income of $595 million for the quarter, of which unrealized gains on equity investments accounted for $756 million of the net profit. Despite the pandemic's impact on the company's operations in 2020, Uber's Q4 results indicate a strong recovery in the industry. The company's CEO, Dara Khosrowshahi, expressed his optimism for the future in a press release, saying, "We ended 2022 with our strongest quarter ever, with robust demand and record margins, “Our global scale and unique platform advantages position us well to accelerate this momentum into 2023.” Dara Khosrowshahi also stated that the company anticipates an increase in the frequency of orders and trips because its efforts to recruit more drivers to its platform have produced a very healthy supply, noting that the business is eroding market share from rivals in both ride-sharing and deliveries. Even though the company's Freight service unit had a difficult quarter due to anticipated headwinds, the company's advertising initiatives are progressing, exceeding a $500 million annual revenue run rate and an advertising base of more than 80% YoY to more than 315,000 small and large businesses. The CEO predicted that it would likely result in $1 billion in revenue for the business this year. According to the CFO, the company’s Ad business continues to perform better than set benchmarks. In a prepared statement, Nelson Chai the CFO of Uber revealed that the company's growing profit margin resulted from its drive for innovation and capital allocation to high-growth business models where they have more substantial leverage. He said, Our capital allocation approach prioritizes investments in attractive markets where we are positioned to win, with a focus on initiatives that strengthen our platform. These initiatives support our expanding profit margins by lowering our customer acquisition costs and increasing the lifetime value of consumers and earners The ride-hailing giant recently rolled out new features, which included Upfront Fares and Upfront Destination, while on the call with analysts and Investors, the CEO said this is the company’s largest release ever and attributed the reduction in cancellations and a higher percentage of fulfillment rates to this new features. The delivery business unit of the company also contributed to its strong earnings. In the statement, the company’s CEO said, “Our Delivery business continued to show resilience, growing at a healthy rate while meaningfully expanding profitability and improving our category position in a majority of our large markets.” On a constant-currency basis, the growth of delivery gross bookings picked up a little from Q3 and increased to 14% YoY overall, with balanced growth in the US & Canada (+14% YoY) and the rest of the globe (+15% YoY). The CEO added that the number of delivery trips, MAPCs, and orders all remained at or very close to all-time highs. With the ongoing vaccination efforts and the gradual easing of pandemic-related restrictions, the company is optimistic about the future and believes it is well-positioned to capture demand for its services. The company’s executives stated that they anticipate adjusted to range from $660 million to $700 million for the first quarter of 2023 and gross bookings to increase by 20% to 24% year over year on a constant currency basis. EBITDA

Uber's Q4 Results Show Positive Traction in Ridesharing, Delivery and Advertising

Los resultados del cuarto trimestre de Uber muestran una tracción positiva en viajes compartidos, entregas y publicidad

Les résultats d'Uber au quatrième trimestre montrent une traction positive dans le covoiturage, la livraison et la publicité

Uber के Q4 परिणाम राइडशेयरिंग, डिलीवरी और विज्ञापन में सकारात्मक आकर्षण दिखाते हैं

Uber の第 4 四半期の結果は、ライドシェアリング、配達、広告でプラスの牽引力を示しています

Resultados do quarto trimestre da Uber mostram tração positiva em compartilhamento de viagens, entrega e publicidade

Kết quả quý 4 của Uber cho thấy lực kéo tích cực trong hoạt động đi chung xe, giao hàng và quảng cáo

优步第四季度的业绩显示在拼车、送货和广告方面的积极影响

In 2009, Garrett Camp and Travis Kalanick founded Uber. Garret Camp was a co-founder of stumble upon and a computer engineer. Travis Kalanick was a co-founder of Red Swoosh, which he sold for $19 million in 2007. The concept arose one winter night following the end of the annual technology conference. When both founders are unable to hail a cab. And they got to thinking: why can't we start this as a business by booking taxis through mobile phones? Garret Camp was so confident in his plan that he purchased the domain name ubercab-com. And he insisted on his co-founder accompanying him. And the rest is history. As of 2021, Uber is present in 72 countries and 10,500 cities. Uber had 118 million monthly active users and 19 million daily average trips by the end of the fourth quarter of 2021. In New York City, Uber provides more than three times the number of rides as yellow taxis. The taxi industry's revolution is divided into two parts: before and after Uber's existence. In this blog, we will look at Uber's business model and revenue channels. Before and After Uber The traditional method of booking a taxi led us to wait longer, which was inconvenient. In addition, the fare was higher when compared to the modern pricing system. These are the issues that customers encounter when booking taxis. People have no idea how uber will solve their problems. The availability of its app on the market increases the likelihood of its effectiveness. Just by using mobile phones, riders can book their taxi. As previously mentioned, uber pricing plans made it simple to acquire new customers who were dissatisfied with the traditional taxi business. Without having any hurdles of waiting for a cab, riders can have easy access to the driver and the same goes for the drivers. As they solve the problem of accessibility it made them unique to the market. Furthermore, the simple app interface increases user engagement. Workflow of Uber 1- Vehicle type and location: The first step starts with choosing the vehicle type and location. 2- Request to taxi drivers: Request sends to drivers when passenger reserve a taxi. 3- Notification to the driver: The request is sent to the driver as a notification. 4- Details of the ride: If the driver accepts the request, the rider will receive the ride details. 5- Payment process: The payment process is done through an app or direct cash. 6- Ratings and reviews: Riders can rate their experience through the review & rating section of the app. Impact of Uber on Riders & Drivers The biggest advantage for Uber is that riders and drivers can both have easy access to themselves. As a driver can accept the rider as they like. This gives the driver freedom of choosing their working hours. By simply having access to a car and mobile phone, drivers can have worked without any prior work experience. Riders do not need to be concerned about their safety because they can easily access the driver's information and previous record. This is where reviews and ratings come into play. Uber has created a new market as this approach helps them to become pioneers in the market. And they started to influence the pricing model of the entire taxi business due to the lack of heavy competition. This becomes a headache for the driver and riders. How Uber makes money The majority of its revenue comes from its commission. For eg, if the app charges $10 to riders, $8 goes to drivers, with the remaining $2 Uber charges as a commission. Uber nearly earned 20-25% as their commission. To increase the Revenue streams, they found another way called surge pricing. What exactly is surge pricing? Uber launched surge pricing in 2014 and it makes them the first to launch this algorithm. It is an algorithm that charges higher than its average fare. It is active in the festive season, bad weather, and night rides. This helps both riders and drivers, as riders are ready to pay when they are in desperate need to travel to their destination. On the driver's side, they are prepared to travel to high-demand areas and take advantage of competitive pricing. For Uber, it's being an additional revenue for them. In simple terms, it was introduced to manage supply & demand and use to capitalize on this opportunity to increase revenue. In-app advertising: Uber has expanded its service to promotional activities. In-app advertising makes them show advertisements through an app. Ads show up after the rider has requested a trip. Some statistics say that 25% of its users see the ad. There are a lot of controversies around (in-app advertising), uber’s co-founder and previous CEO Travis Kalanick was opposed to the idea of in-app advertising, claiming that it would ruin the user experience. Moreover, it generates additional revenue for Uber. Uber customer segment As Uber steps into the global market, they realize that it is important to target every customer to broaden its market. That is why they come up with different product lineups. Below mentioned are some of its examples: Uber x = Four-seat sedan Uber XL= XUV or van Uber pool = Share rides with a person who is headed to the same destination. Uber moto = Bike taxi Uber Auto = Auto rickshaw Uber premium = High-end luxury vehicle Uber knows how to treat every segment of its users. This gives a bigger hands-on user acquisition. In the initial stage of the launch, uber struggled to acquire new drivers for their app. Because drivers are satisfied with their earnings. So, uber plans to come up with a marketing campaign called referral marketing. It enables drivers to receive referral bonuses and riders to give their friends free rides while earning credit for themselves, thereby acquiring both driver and rider becomes faster and easier. Uber value proportion Their slogan says for riders - “We will always give you a ride when you need it.” For drivers - “We will always give you passengers when you want them.” Value proportion for Riders: Affordable pricing Reduces waiting time Service available 24*7 Riders get an estimation of how much they have to pay Easy access to drivers Value proportion for : Drivers Easy access to riders Don’t need any work experience Flexible working hours Part-time earnings Uber customer acquisition One of the difficult aspects of any business is acquisition. Convenient booking and pricing increase its brand popularity through word of mouth. Other than spending a huge amount on the advertisement they focus on solving a customer pain point. The following are some of the channels through which they obtained their users: Through an app Word of mouth Social media Advertisement Uber key activity These are the three main activities that uber has its primary focus: Developing and maintaining an app Improving engagement between rider and driver Marketing & customer service Driver onboarding Final words We have arrived at the final section. I hope I have covered overall on Uber's business model and revenue channel. I hope you find this interesting. See you all in the next blog.

Understanding How Uber Works

Very often when people talk about security, the discussion of password managers or vaults come up. These can be useful for individuals. However, they carry some real risks for companies, if they’re not carefully considered. , and by all accounts from the attacker thoroughly so. A password vault system called Thycotic came heavily into play along with some other measures designed to add rather than remove security. Uber was recently breached https://hackernoon.com/how-an-18-year-old-teen-breached-uber-without-hacking-a-single-system?embedable=true There are a few things I want to start off with: the technology and tools themselves are not at fault here, instead it’s down to the implementation of them and the wider design of Uber’s systems password managers and vaults are used interchangeably, but usually a password vault will be more of an enterprise system for a company to protect credentials across the business rather than for a single user security is complicated, and when it hasn’t been designed in from the start you end up with large vulnerabilities that mean the smallest mistake can become a massive breach with very little notice What happened in the Uber hack? We start off with notification fatigue. The attacker, supposedly a 17 year old “TeaPot” from the UK found credentials (likely purchased online) of an Uber contractor and began sending multi factor authentication requests to them repeatedly. This is rapidly becoming a common attack, simply trying to annoy people into accepting the notification, although in this case they also sent a message via WhatsApp claiming to be from Uber IT and telling the contractor that there was an error, and if they accepted the notification it would stop the alerts. After the contractor accepted the alert TeaPot claims to have accessed the intranet and found a script with admin credentials for the Thycotic Secrets Vault Uber uses to manage their credentials. Admin credentials could mean everything in the password vault was available to the attacker, and this seems to be what happened. Supposedly it included access to the bug bounty programme, meaning TeaPot gained access to unfixed vulnerabilities in Uber’s apps and systems. So are password vaults bad? Here’s the problem. Security is complicated and managing credentials is tough. At the scales Uber and other unicorns work at, many not built for security from the start they are effectively working on a foundation of quicksand. Desperately trying to retrofit security into systems never designed for it while still trying to operate as a business and keep up with investor demands. Password vaults such as Thycotic are not, themselves, a bad idea, but what would have helped in Uber’s case? You’ll see a lot of talk about zero trust principles, which mean not trusting any one device in a network to access anything, but while these principles are talked about a lot they are impossibly hard to implement if they’re not built in from the start. Not having a password vault is another option, and that might have helped simply because it would mean less likelihood of having all those credentials in one place. On the other hand, it means users are much more likely to use weak passwords in the first place and to store them in insecure ways such as on a spreadsheet or text file. If they’re implemented properly, password vaults make managing secure systems much, much easier for users. The real fault here was in having admin credentials to the password vault in the first place, instead individual accounts should be created with access only to the credentials they need. No external contractor, no matter how trusted, should ever have access to that level of credentials - they simply do not need it. I wouldn’t be comfortable even with the most trusted of employees having that sort of access. It’s the type of thing you split into multiple pieces, spread between several members of the board, and lock in a safe for emergencies, such as your whole IT team being abducted by aliens. Should I use a password vault? One thing that did come up after the attack was a lot of security product vendors selling their solution as the one and only that would have prevented it. At best, these should be completely ignored, as the weaknesses that led to the breach were (and almost always are) complex and multifaceted with no easy fix. The other was that a lot of people were questioning whether password vaults or managers were suddenly a new and massive risk to take, and whether they were safe to use. Image via URegina The simple answer is yes, if it’s useful and makes sense for you. A well-set-up vault lets you use much more secure passwords, rotate them regularly, and manage them well. Many enterprise secret vaults will change passwords after each use and manage a lot more than user credentials such as certificates and other private keys. The more complex answer is that any tool you use to simplify security will introduce trade offs and their own risks to an environment. A password vault will give you more secure passwords and better management of credentials, but the trade off is that all of these credentials in one place make it a tempting target for an attacker and can cause a minor breach to become more serious fast.

Uber & Thycotic: Are Password Vaults a Huge Security Vulnerability?

Uber y Thycotic: ¿Son las bóvedas de contraseñas una gran vulnerabilidad de seguridad?

Uber et Thycotic : les coffres-forts de mots de passe sont-ils une énorme vulnérabilité de sécurité ?

उबेर और थाइकोटिक: क्या पासवर्ड वॉल्ट एक बड़ी सुरक्षा भेद्यता है?

Uber & Thycotic: パスワード保管庫は巨大なセキュリティ脆弱性ですか?

Uber e Thycotic: os cofres de senha são uma enorme vulnerabilidade de segurança?

Uber & Thycotic: Kho chứa mật khẩu có phải là lỗ hổng bảo mật lớn không?

Uber & Thycotic：密码库是一个巨大的安全漏洞吗？

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In this article, I would like to tell you how I solved the following task, namely the generation of DTOs using the JSON documentation that springwolf generates. @dstepanov Read More. Every Career Starts with a Leap of Faith: Navigating a Career in Content Creation By [ 7 Min read ]
After being diagnosed with a chronic illness at the age of 14, she worked diligently to bring positivity to the world through her art, personality, and content. @scott-d.-clary Read More. Ubers Secret Algorithm to Calculate Fares By [ 6 Min read ]
Uber has quietly changed the way it pays drivers in several major cities across the U.S., using a new feature it’s calling “Upfront Fares.” @TheMarkup Read More. How an 18-Year-Old Teen Breached Uber Without Hacking a Single System By [ 8 Min read ]
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The Noonification: Ubers Secret Algorithm to Calculate Fares (9/22/2022)

Uber has quietly changed the way it pays drivers in several major cities across the U.S., using a new feature it’s calling “Upfront Fares.” Instead of paying drivers for trips based on just time and distance, it’s now to calculate the fare. using an algorithm “based on several factors” What all of those factors are is unclear. Uber has to determine how much passengers pay, which is one of the reasons riders sometimes see vast price fluctuations. long used an upfront pricing algorithm The company says the new feature provides drivers with more transparency. They see more details of a prospective ride before accepting it, such as the fare and pick-up and drop-off locations, which is something drivers say they’ve been asking for. In the past, most drivers wouldn’t receive this information until after they accepted a ride. Uber spokesperson Harry Hartfield said upfront fares are about giving drivers “more control and choice” but will include a “balancing” of payments. That means, he said, drivers will make less money for longer trips but should earn more on shorter trips. Some drivers say, however, that they’ve mostly seen lower earnings overall since the change. On top of that, they say, it seems like Uber is taking a bigger cut of fares. “Before, you could guestimate—back of envelope calculate—and see that [the trip is] this far and this long and figure out you’ll make this much,” said Sam Vance, who’s been a full-time UberX and Lyft driver in Columbus, Ohio, for more than four years. Now, “it’s not based on anything. There’s no rhyme or reason to it.” Uber has long said the average amount it . But Vance shared screenshots with The Markup of two recent trips he did for Uber that show the company took far more. takes from fares is about 25 percent One shows a customer paid $30 for a 20.9-mile trip, Vance earned $14, Uber got $13, and the rest went to sales tax. The other trip, which was 8.8 miles and included an airport drop, the customer paid $22, Vance got $6, Uber took $9, and the remainder went to airport fees and sales tax. When asked about its take from Vance’s trips, Uber’s Hartfield said these trips were not necessarily representative of Uber’s usual take. Vance said that Uber often takes around half the fare. 2. 3. Before Uber’s change in pay structure, Vance said he’d normally average around $1 per mile once time and distance were calculated, especially if he was driving on the highway. So, the 20.9-mile trip would have earned him about $21, and the 8.8-mile trip would have brought in roughly $9. “Some drivers are really looking forward to this because they think it’s going to be a positive change,” Vance said. “But it’s not what you think it is.” The Rideshare Guy blog (which partners with Uber and receives commissions for signing up new drivers for the company) was the first publication to . Reuters additionally . detail Uber’s new pay structure reported on it last week According to both sources, Uber has in states including Texas, Florida, and throughout the Midwest. It appears the company initially started about six months ago, including Columbus, where Vance lives. rolled out upfront fares to a total of 24 U.S. cities testing the pay structure in a handful of cities “Black Box Algorithms” Uber isn’t the first gig company to experiment with algorithms to calculate driver earnings. A few years ago, Instacart, DoorDash, and Shipt started calculating pay for their delivery couriers using what workers call “black box algorithms.” Anecdotally, many couriers for those delivery companies have said the have made it . They also say over time. seemingly arbitrary fluctuations of the pay algorithms harder to predict and figure out their earnings they’ve seen their pay decline Worker advocates say using concrete factors, like time and mileage, helps drivers and couriers better assess if a trip is worth taking and understand how they’re being compensated. The more opaque the fare calculations, the more drivers, regulators, and the public have a hard time holding the gig companies accountable to fair and transparent pay standards, said Amos Toh, a senior researcher for Human Rights Watch who . studies the effects of artificial intelligence and algorithms on gig work “Uber didn’t come out and say this is going to be algorithmic, but the criteria that they are using—a range of factors and things that aren’t specified—could indicate that the fares are going to disappear behind a black box algorithm,” Toh said. “When you put a fare calculation behind a black box algorithm, it’s possible to have the capacity to learn from driver behavior … and actually for a ride.” learn what is the lowest rate a driver will take “We don’t have any evidence that Uber is doing this,” Toh added. “But the real problem is the secrecy, because it makes it impossible to verify.” Uber’s Hartfield didn’t respond to questions about why Uber changed its pay structure in these markets, when the pilot first began, or whether it plans to take it nationwide. He also didn’t respond to questions about what cities currently have upfront fares or how Uber’s algorithm calculates driver fares. When asked for all of the factors that are taken into account to calculate drivers’ fares, Hartfield said in an emailed statement, “Rather than just the time and distance of the trip, upfront fares are based on a much more comprehensive set of factors including base fares, estimated trip length and duration, real-time demand at the destination, and surge pricing. While earnings are subject to seasonal demand patterns and the types of trips a driver chooses to take, we haven’t observed an earnings impact due to this pilot in cities that have had upfront fares for more than six months.” He didn’t respond to questions about whether this was the complete list of factors or whether there were more factors. Hartfield said The Markup could “learn more about the pilot” from the by The Rideshare Guy and also sent a by Uber about upfront fares, saying, “It’s worth looking through the comments under the video, most of which are from drivers saying they’d like to see these changes in more markets.” blog post link to a YouTube video The video has several comments from drivers saying they’re happy to see more trip information before accepting a fare. Other commenters say they don’t like the idea of being paid less for longer rides. Several Reddit threads and comments on driver forums have also popped up, with drivers who’ve tested the feature saying they’ve often seen , , and an . lower fares confusing fare drops during rides overall decrease in rides Along with upfront fares, Uber has also rolled out a companion feature in those 24 cities called “Trip Radar.” The way it works is that Uber shows a trip to several drivers at once, and whoever accepts the ride first gets it. Vance said he usually only has a second or two to see it and click, so he doesn’t have time to see the upfront details right away. “It’s kind of a moot point because it comes up so fast on the screen, and there are four or five other drivers tapping on it,” Vance said. “It’s like Hungry Hungry Hippos, and everyone is tapping.” Hartfield didn’t respond to request for comment on drivers not having time to see upfront details with Trip Radar and having to compete for rides. Vance said recently, in his haste to accept a ride, he got stuck on a five-hour round-trip drive to Cleveland. For that trip, he earned just $90. Before Uber instituted upfront fares, Vance said he liked doing longer trips. Back then, he said, a trip to Cleveland would usually net him at least $140. “Because there’s no longer a rate card, that’s interrupted the way drivers drive. Your strategy just has to be different,” Vance said. “Now you have to stay out longer, and it takes a lot more to make money, and you don’t make as much.” Credits: Dara Kerr Photo by on Barna Bartis Unsplash Also published here

Uber's Secret Algorithm to Calculate Fares

Algoritmo secreto de Uber para calcular tarifas

L'algorithme secret d'Uber pour calculer les tarifs

किराए की गणना करने के लिए उबेर का गुप्त एल्गोरिथम

運賃を計算する Uber の秘密のアルゴリズム

Algoritmo secreto do Uber para calcular tarifas

Thuật toán bí mật của Uber để tính giá vé

优步计算票价的秘密算法

With the latest update now Uber is showing trip destinations to drivers before they decide to accept a ride to enable them to make informed choices. You will likely not have to pay Uber trip cancellation fee and the driver is unlikely to cancel the trip either. The thing now from change from here, it has been always hard to predict if a driver would cancel a ride or not as the conversation of user-driver used to be on a phone call. Since the driver is now more informed about the pick and drop location of the user and is incentives separately for the distance traveled to pick up the user, . the focus now shifts from cancellation to driver accepting a ride Let’s understand from a Data Science (Machine Learning) perspective what happens behind the scene to match user requests to a driver whose probability to accept the ride is high and get your request fulfilled in the minimum time possible. In summary, to find the best cab drivers for you — within a few seconds; these ride-hailing companies (Uber, Lyft, Ola, Rapido, etc.) run a matching algorithm and also check a driver’s ride acceptance probability before pushing a request to them. In this Newsletter, we shall discuss how we can build a driver ride acceptance probabilistic model. Objective: Predict if a driver will accept ride request or not and find the probability of acceptance? Characteristics / Features Required In order to figure out the features required to solve this problem in a ride-hailing business, a data scientist must be well-versed with domain knowledge. Product thinking is always important for a data scientist. 1. Trip Drive to User (Client) Distance (Driver to Pickup Distance) Time of the Day (Morning / Afternoon / Evening / Late Night) Trip duration/distance (Pick up to Drop Distance) Payment method (some drivers prefer Cash Mode more than online payments) Destination of the client (drivers don’t like to go to a destination where they will have to struggle to get their next client) Ride Type — Pool request or Normal request 2. Driver a) Enroute or Available Whether the driver is available (no rides) If the driver is en route — the trip is about to end or in the middle of it b) Historic Features In the last one week/month avg. number of rides accepted rate Total trips completed throughout the day — If the driver has achieved his incentive target of the day or not Current days acceptance rate (acceptance rate = Number of requests accepted / Total requests received) 3. Vehicle Type Cab / Auto Rickshaw / Bike (based on vehicle type some drivers don’t accept client pickups in lonely areas — safety concerns) Many Bike / Auto Rickshaw drivers don’t prefer ride requests of > 10kms 4. Rider (Client) Rider Rating (driver doesn’t like to deal with clients below 4 ratings) Rider gender (some drivers don’t accept ride requests based on request time and client gender) Rider Image (interesting experiment someone did by replacing his image with a zombie image and got less driver acceptance; proving the image of the client to the driver also matters) Interesting read profile image matters on both (driver and rider) side 😂: ‘Zombie’ drivers are scamming people out of cash with horrible profile pictures 5. Traffic Based on request time — drivers sometimes don’t like to accept rides in heavy traffic zones (the duration of the trip to complete or to reach the client — depends on traffic in the region) 6. Special Events (occasional change) Weather — Rainy Day / Sunny Covid restrictions in that Area (Quarantine zone) Festival Day based on region — Holi, Diwali, Christmas, etc. Modeling We now have a rich feature set that can help us predict whether a driver will accept a client’s ride request or not. We use standard statistical machine learning supervised classification algorithms(with spot-checking): Logistic Regression (Linear Model) Decision Tree (Non-Linear Model) Bagging Classifier — Random Forest Classifier (Ensemble Model) Boosting Classifier — LightGBM, XGBoost, etc. : AUC-ROC, F-beta score (beta = 2; if Recall is twice important as Precision) Model Metrics Conclusion I hope you understood the business problem and can relate to the features we picked for modeling out the patterns. While there is no silver bullet solution and these problems are way more complex, our aim was to improve the user experience and minimize the user-driver matching time as even a millisecond of change in the driver-user matching algorithm can help save millions of dollars. According to a paper entitled The Cost of Latency in High-Frequency Trading, a 1-millisecond advantage in latency can be worth upwards of $100 million per year. I hope you learned something new from this post. If you liked it, hit 👏, subscribe to my newsletter, and share this with others. Stay tuned for the next one! Connect, Follow or Endorse me on if you found this read useful. LinkedIn I am open to Gigs or Consults you can reach out to me on LinkedIn: https://www.linkedin.com/in/shaurya-uppal/ Also published . here

Using Machine Learning to Build a Ride Acceptance Model for Uber

In the we introduced Uber’s Presto use cases and how we collaborated to implement Alluxio local cache to overcome different challenges in accelerating Presto queries. The second part discusses the improvements to the local cache metadata. previous blog, File Level Metadata for Local Cache Motivation First, we want to prevent stale caching. The underlying data files might be changed by the third-party frameworks. Note that this situation might be rare in Hive tables but very common in Hudi tables. Second, the daily reads of unduplicated data from HDFS can be large, but we don’t have enough cache space for caching all the data. Therefore, we can introduce scoped quota management by setting a quota for each table. Third, metadata should be recoverable after server restart. We have stored metadata in the local cache in memory instead of disk, which makes it impossible to recover metadata when the server is down and restarted. High-Level Approach Therefore, we propose the File Level Metadata, which holds and keeps the last modified time and the scope of each data file we cached. The file-level metadata store should be persistent on disk so the data will not disappear after restarting. With the introduction of file-level metadata, there will be multiple versions of the data. A new timestamp is generated when the data is updated, corresponding to a new version. A new folder storing the new page is created corresponding to this new timestamp. At the same time, we will try to remove the old timestamp. Cache Data and Metadata Structure As shown above, we have two folders corresponding to two timestamps: timestamp1 and timestamp2. Usually, when the system is running, there will not be two timestamps simultaneously because we will delete the old timestamp1 and keep only timestamp2. However, in the case of a busy server or high concurrency, we may not be able to remove the timestamp on time, in which case we may have two timestamps at the same time. In addition, we maintain a metadata file that holds the file information in protobuf format and the latest timestamp. This ensures that Alluxio’s local cache only reads data from the latest timestamp. When the server restarts, the timestamp information is read from the metadata file so that the quota and last modified time can be managed correctly. Metadata Awareness Cache Context Since Alluxio is a generic caching solution, it still needs the compute engine, like Presto, to pass the metadata to Alluxio. Therefore, on the Presto site, we use the HiveFileContext. For each data file from the Hive table or Hudi table, Presto creates a HiveFileContext. Alluxio makes use of this information when opening a Presto file. When calling openFile, Alluxio creates a new instance of PrestoCacheContext, which holds the HiveFileContext and has the scope (four levels: database, schema, table, partition), quota, cache identifier (i.e., the md5 value of the file path), and other information. We will pass this cache context to the local file system. Alluxio can thus manage metadata and collect metrics. Per Query Metrics Aggregation on Presto Side In addition to passing data from Presto to Alluxio, we can also call back to Presto. When performing query operations, we will know some internal metrics, such as how many bytes of data read hit the cache and how many bytes of data were read from external HDFS storage. As shown below, we pass the HiveFileContext containing the PrestoCacheContext to the local cache file system (LocalCacheFileSystem), after which the local cache file system calls back (IncremetCounter) to the CacheContext. Then, this callback chain will continue to the HiveFileContext, and then to RuntimeStats. In Presto, RuntimeStats is used to collect metrics information when executing queries so that we can perform aggregation operations. After that, we can see the information about the local cache file system in Presto’s UI or the JSON file. We can make Alluxio and Presto work closely together with the above process. On the Presto side, we have better statistics; on the Alluxio side, we have a clearer picture of the metadata. Future Work Performance Tuning Because the callback process described above makes the CacheContext’s lifecycle grow considerably, we have encountered some problems with rising GC latency, which we are working to address. Adopt Semantic Cache (SC) We will implement Semantic Cache (SC) based on the file-level metadata we propose. For example, we can save the data structures in Parquet or ORC files, such as footer, index, etc. More Efficient Deserialization To achieve more efficient deserialization, we will use flatbuf instead of the protobuf. Although protobuf is used in the ORC factory to store metadata, we found that the ORC’s metadata brings more than 20-30% of the total CPU usage in Alluxio’s collaboration with Facebook. Therefore, we are planning to replace the existing protobuf with a flatbuf to store cache and metadata, which is expected to improve the performance of deserialization significantly. To summarize, together with the previous blog, this two-part blog series shares how we created a new caching layer of the hot data needed for our Presto fleet based on recent open-source collaboration between Presto and Alluxio communities at Uber. This architecturally simple and clean approach can significantly reduce HDFS latency with managed SSD and consistent hashing-based soft affinity scheduling. Join 9000+ members in our community to learn more. slack channel About the Authors is a senior software engineer at Uber’s interactive analytics team, focusing on Presto. Before joining Uber, Chen was a staff software engineer at LinkedIn’s Big Data platform. Chen is also a committer and PMC member of Apache Hadoop. Chen holds two master’s degrees from Duke University and Brown University Chen Liang is a software engineer from Alluxio and is the committer of PrestoDB. Before Alluxio, he was the Tech Lead of the Presto team in Twitter, and he built large-scale distributed SQL systems for Twitter’s data platform. He has twelve-year experience working on performance optimization, distributed caching, and volume data processing. He received his Ph.D. in computer engineering from Syracuse University on the symbolic model checking and runtime verification of distributed systems. Dr. Beinan Wang Also published here.

The Design and Implementation of Presto Local Cache at Uber

El diseño e implementación de Presto Local Cache en Uber

La conception et la mise en œuvre de Presto Local Cache chez Uber

उबेर में प्रेस्टो लोकल कैश का डिजाइन और कार्यान्वयन

Uber での Presto Local Cache の設計と実装

O design e a implementação do Presto Local Cache na Uber

Thiết kế và triển khai Presto Local Cache tại Uber

Uber Presto 本地缓存的设计与实现

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 always find a Uber? All that while also managing all the drivers?! Well, we will answer exactly that in the video... References ►Read the full article: ►Uber blog post: ►What are transformers: ►Linear Transformers: ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/uber-deepeta/ https://eng.uber.com/deepeta-how-uber-predicts-arrival-times/ https://youtu.be/sMCHC7XFynM https://arxiv.org/pdf/2006.16236.pdf https://www.louisbouchard.ai/newsletter/ Video transcript 0:00 how can uber deliver food and always 0:02 arrive on time or a few minutes before 0:05 how do they match riders to drivers so 0:07 that you can always find a uber all that 0:10 while soon managing all the drivers we 0:12 will answer these questions in this 0:14 video with their arrival time prediction 0:16 algorithm deep eta deep eta is uber's 0:20 most advanced algorithm for estimating 0:22 arrival times using deep learning used 0:25 both for uber and uber eats deep eta can 0:28 magically organize everything in the 0:30 background so that riders drivers and 0:32 food are fluently going from point a to 0:34 point b as efficiently as possible many 0:37 different algorithms exist to estimate 0:40 travel on such road networks but i don't 0:42 think any are as optimized as uber's 0:45 previous arrival time prediction tools 0:47 including uber were built with what we 0:50 call shortest path algorithms which are 0:52 not well suited for real-world 0:54 predictions since they do not consider 0:56 real-time signals for several years uber 0:59 used xgboost a well-known gradient 1:02 boosted decision tree machine learning 1:04 library xjboost is extremely powerful 1:07 and used in many applications but was 1:09 limited in uber's case as the more it 1:11 grew the more latency it had they wanted 1:14 something faster more accurate and more 1:16 general to be used for drivers riders 1:18 and food delivery all orthogonal 1:20 challenges that are complex to solve 1:22 even for machine learning or ai 1:25 here comes deep eta a deep learning 1:28 model that improves upon xg boosts for 1:30 all of those oh and i almost forgot 1:33 here's the sponsor of this video 1:36 myself please take a minute to subscribe 1:39 if you like the content and leave a like 1:41 i'd also love to read your thoughts in 1:43 the comments or join the discord 1:45 community learn ai together to chat with 1:47 us let's get back to the video 1:49 deep eta is really powerful and 1:51 efficient because it doesn't simply take 1:53 data and generate a prediction there's a 1:56 whole preprocessing system to make this 1:58 data more digestible for the model this 2:00 makes it much easier for the model as it 2:02 can directly focus on optimized data 2:05 with much less noise and far smaller 2:07 inputs a first step in optimizing for 2:10 latency issues this pre-processing 2:12 module starts by taking map data and 2:14 real-time traffic measurements to 2:16 produce an initial estimated time of 2:18 arrival for any new customer request 2:21 then the model takes in these 2:23 transformed features with the spatial 2:25 origin and destination and time of the 2:27 request as a temporal feature but it 2:29 doesn't stop here it also takes more 2:32 information about real-time activities 2:34 like traffic weather or even the nature 2:36 of the request like delivery or ride 2:39 share pickup all this extra information 2:41 is necessary to improve from the 2:43 shortest path algorithms we mentioned 2:45 that are highly efficient but far from 2:47 intelligent are real world proof and 2:50 what kind of architecture does this 2:52 model use you guessed it a transformer 2:54 are you surprised because i'm definitely 2:56 not and this directly answers the first 2:59 challenge which was to make the model 3:01 more accurate i've already covered 3:03 transformers numerous times on my 3:04 channel so i won't go into how it works 3:07 in this video but i still wanted to 3:08 highlight a few specific features for 3:11 this one in particular first you must be 3:13 thinking but transformers are huge and 3:16 slow models how can it be of lower 3:18 latency than xg boost well you will be 3:21 right they've tried it and it was too 3:23 slow so they had to make some changes 3:26 the change with the biggest impact was 3:28 to use a linear transformer which scales 3:30 with the dimension of the input instead 3:33 of the input's length this means that if 3:35 the input is long transformers will be 3:38 very slow and this is often the case for 3:40 them with as much information as routing 3:42 data instead it scales with dimensions 3:45 something they can control that is much 3:47 smaller another great improvement in 3:49 speed is the discretization of inputs 3:52 meaning that they take continuous values 3:53 and make them much easier to compute by 3:56 clustering similar values together 3:58 discretization is regularly used in 4:00 prediction to speed up computation as 4:02 the speed it gives clearly outweighs the 4:04 error that duplicates values may bring 4:07 now there is one challenge left to cover 4:10 and by far the most interesting is how 4:13 they made it more general here is the 4:15 complete deep eta model to answer this 4:18 question there is the earlier 4:19 quantization of the data that are then 4:22 embedded and sent to the linear 4:24 transformer we just discussed then we 4:26 have the fully connected layer to make 4:28 our predictions and we have a final step 4:31 to make our model general the bias 4:33 adjustment decoder it will take in the 4:36 predictions and the type features we 4:38 mentioned at the beginning of the video 4:40 containing the reason the customer made 4:42 a request to uber to a render prediction 4:44 to a more appropriate value for a task 4:46 they periodically retrain and deploy 4:49 their model using their own platform 4:51 called michelangelo which i'd love to 4:53 cover next if you're interested if so 4:56 please let me know in the comments and 4:58 voila this is what uber currently use in 5:01 their system to deliver and give rides 5:03 to everyone as efficiently as possible 5:07 of course this was only an overview and 5:09 they used more techniques to improve the 5:11 architecture which you can find out in 5:13 their great blog post linked below if 5:16 you're curious i also just wanted to 5:18 note that this was just an overview of 5:20 their arrival time prediction algorithm 5:22 and i am in no way affiliated with uber 5:25 i hope you enjoyed this week's video 5:28 covering a model applied to the real 5:30 world instead of a new research paper 5:32 and if so please feel free to suggest 5:35 any interesting applications or tools to 5:37 cover next i'd love to read your ids 5:39 thank you for watching and i will see 5:41 you next week with another amazing paper [Music]

How Uber Uses AI to Improve Deliveries

Cómo utiliza Uber la IA para mejorar las entregas

Comment Uber utilise l'IA pour améliorer les livraisons

डिलीवरी को बेहतर बनाने के लिए Uber AI का इस्तेमाल कैसे करता है

Uber が AI を使用して配達を改善する方法

Como a Uber usa IA para melhorar as entregas

Cách Uber sử dụng AI để cải thiện việc giao hàng

优步如何使用人工智能来改善交付

We've all assisted the consistent growth of Uber. They even expanded their business to the food delivery branch, which has developed more and more throughout the pandemic. However, we also know how conflicting it was between Uber drivers and cab drivers. So it was with great curiosity that we approached the possibility of a truce between them in this slogging thread. This Slogging thread by Sara Pinto, Jack Boreham and Mónica Freitas occurred in slogging's official #random channel, and has been edited for readability. Sara Pinto Mar 29, 2022, 6:48 PM Truces between uber drivers and taxis? https://www.nbcnews.com/tech/tech-news/years-rivalry-uber-puts-nyc-taxi-cabs-app-rcna21428 Sara Pinto Mar 29, 2022, 6:49 PM "Uber, hit by driver shortages and a surge in food delivery requests during the pandemic, will list New York City taxi cabs on its app, a partnership that until recently would have been unthinkable with both camps fighting ferociously for the same customers." Sara Pinto Mar 29, 2022, 6:49 PM "After a period in which waits for an Uber ride grew longer due to a driver shortage, the partnership will boost the number of rides available, and it gives NYC cab drivers access to a massive pool of commuters with an Uber app on their phones." Sara Pinto Mar 29, 2022, 6:49 PM "There had been hints tensions between Uber and taxi services had begun to thaw as Uber expanded aggressively into the very lucrative food delivery business and needed a growing supply of delivery drivers." "During the pandemic, Uber’s food deliveries outpaced rides given to humans as millions sheltered at home. Gross bookings for delivery services at Uber reached $13.4 billion in the final quarter of 2021. That’s compared with $11.3 billion in gross bookings for Uber rides." Sara Pinto Mar 29, 2022, 6:56 PM Uber has unstoppable growth. Making this agreement with taxi drivers is a chance to expand even more and for everyone to remain in business. Plus, I believe it allows the cab drivers to gain more opportunities since there's the food delivery business. Sara Pinto Mar 29, 2022, 6:57 PM Jack Boreham Abeer Limarc Ambalina, what are your thoughts on this? Could this backfire? Would you like to see this in your country/city? Jack Boreham Mar 30, 2022, 11:20 AM Sara Pinto, I definitely do! I hope Uber starts to dominate and get a monopoly. There needs to be a standardized taxi service that is cheap and not dodgy Sara Pinto Mar 31, 2022, 5:03 PM Jack Boreham, I absolutely agree. Uber obligates drivers to follow conduct that brings us safety and quality Sara Pinto Mar 31, 2022, 5:03 PM In my opinion, this is a way to deal with two issues at the same time: the tension with the taxi drivers and their shortage of employees. This is a great solution Sara Pinto Mar 31, 2022, 5:05 PM Right now, in my city in Portugal, I'm seeing fewer Uber drivers as well, so at this point, I wish they applied here too Mónica Freitas Apr 1, 2022, 1:01 PM Sara Pinto, I guess this will mean fewer fights and tension between Uber drivers and taxis. I like this solution. It helps to control price limits and includes taxi drivers in a market that was pushing them out. Hopefully, this spreads and we get more data; I would like to see the difference this measure made in numbers. Sara Pinto Apr 1, 2022, 7:14 PM Mónica Freitas, exactly my thoughts! I hope other companies step up their game so Uber doesn't fully control the market. There still needs to exist competition, but with companies that operate the same way, such as Bolt Sara Pinto Apr 1, 2022, 7:15 PM Jack Boreham, you wish for a monopoly, but don't you think that would bring disadvantages to the clients? Mónica Freitas Apr 7, 2022, 12:30 PM Sara Pinto my worry is when it comes to safety. How will these platforms verify their drivers? How can they make sure that it is safe for clients?! Sara Pinto Apr 7, 2022, 2:08 PM Mónica Freitas, we always have the chance to rate and report the drivers. I think that's one of their methods, and as far as I know, it works! Mónica Freitas Apr 8, 2022, 9:44 AM Sara Pinto, I wonder if there's some previous assessment... Because I do know that for someone to be a taxi driver there's still a bit of bureaucracy involved, which differs from the process of becoming an Uber driver Mónica Freitas Apr 8, 2022, 9:45 AM Sara Pinto this whole topic is putting the song "Uber driver" from Mischlawi playing nonstop in my head 😂 😂 1 Sara Pinto Apr 8, 2022, 12:06 PM Mónica Freitas, I just checked the Uber driver requirements, and it's quite easy to be one. Since the taxi drivers are entering this company, I assume they maintain this process. They probably won't add any other condition Mónica Freitas Apr 11, 2022, 10:10 AM Sara Pinto one of the things I remember taxi drivers complaining about was the high fees and taxes they had to pay. Maybe by collaborating with Uber those will decrease. Or maybe there won't be any more taxi drivers and just Uber drivers 🔥 1

A Much-Needed Truce Between Uber Drivers and Taxis

Una tregua muy necesaria entre los conductores de Uber y los taxis

Une trêve bien nécessaire entre les chauffeurs Uber et les taxis

उबर ड्राइवरों और टैक्सियों के बीच एक बहुत जरूरी समझौता

Uber の運転手とタクシーの間に切望されていた休戦

Uma trégua necessária entre motoristas de Uber e táxis

Một thỏa thuận rất cần thiết giữa tài xế Uber và taxi

优步司机和出租车之间急需的休战

Photo by on Paul Hanaoka Unsplash For the first time in five years of driving for Uber and Lyft in Minneapolis, Tom LaDuke said he’s been thinking twice before heading out. Ride-hail drivers have in a surge of carjackings throughout the city over the past couple of months. increasingly become targets Officer Garrett Parten of the Minneapolis Police Department told The Markup that the department had tracked nearly 50 carjackings of Uber and Lyft drivers since mid-August. Twelve such incidents happened in the third week of October alone. LaDuke said these numbers are unsettling. “Over the last three weeks I have not driven as much as I did before,” he said. “I’m concerned about my safety.” The incidents tend to follow a pattern, Parten said. Typically, an individual uses a stolen phone to hail a ride through Uber’s or Lyft’s app. When the driver arrives, someone meets the car and asks the driver to wait a few minutes. Shortly after, a group of “armed individuals” appears, surrounds the vehicle, and demands the driver get out. Along with the car, the group also usually takes the driver’s wallet and phone and gets the phone’s security code to . access the driver’s various accounts to transfer out money “Some drivers have been assaulted, including being pistol whipped,” read a issued by the Minneapolis Police Department on Oct. 22. “Ride-Share operators need to take extra precautions to stay safe.” citywide alert Both Uber and Lyft said they’re working to improve safety on their apps. “These reports are concerning,” said Uber spokesperson Carly DeBeikes. “Safety is a top priority for us and we are constantly working to use technology to enhance safety on the app for riders and drivers.” Lyft spokesperson Ashley Adams said, “While these horrific crimes are by no means unique to rideshare, the safety of our community is fundamental to Lyft…. We continuously invest in new features and policies to help protect drivers.” Adams and DeBeikes said the companies were working closely with the Minneapolis Police Department on the issue. But Parten said the police department had reached out to Uber and Lyft, after noting the carjacking trend, to get the companies to provide drivers with safety tips, and “they just weren’t very responsive.” The carjackings of Uber and Lyft drivers in Minneapolis fit into a . Police departments from to to have said they’ve seen an uptick of all types of carjackings during the pandemic. larger nationwide trend Chicago Cleveland Washington, D.C., In Minneapolis, carjackings and attempted carjackings increased by 339 percent over the last two years, going from 104 in 2019 to 457 so far in 2021, according to the police department. There were 401 reported carjackings in 2020. And Uber and Lyft drivers are frequent targets all over the country. In July, The Markup used police reports, local news articles, and driver interviews to . identify 124 cases of ride-hail drivers being attacked Eleven of those drivers were killed during the assaults, including Ahmed Badal, a 35-year-old Somali immigrant who was . Lyft’s Adams said the company has “attempted to contact Ahmed’s family to offer our support.” shot in April while driving for Lyft in Minneapolis Over the past few months, The Markup has identified dozens more cases of Uber and Lyft drivers being carjacked in cities including , , and . At least three more drivers have been killed. Atlanta Chicago Kansas City These numbers are far from comprehensive. Uber and Lyft have repeatedly declined to provide The Markup data on the number of carjackings involving their drivers, and most police departments don’t compile stats on carjackings that happen specifically to ride-hail drivers. Not all drivers report the incidents either. The Minneapolis Police Department’s compilation of roughly 50 carjackings since August is rare concrete evidence of the high rate at which ride-hail drivers have been targeted. Uber and Lyft treat their drivers as independent contractors rather than employees, so when carjackings occur, drivers say they’re usually . They don’t have benefits like workers’ compensation or sick leave, and losing their cars can also mean losing their livelihood. left to fend for themselves “As soon as a carjacking is reported to us, we immediately reach out to the driver to offer our support,” Lyft’s Adams said. Several drivers, however, told The Markup that after carjackings . they’ve been offered little to no help The majority of these reported carjackings happened through Uber’s and Lyft’s apps. Drivers don’t have much say in whom they pick up and where they go, and the apps make it fairly simple for passengers to to hail rides. create fake accounts with fake names In most cases, rider identification isn’t required, and things like email addresses and phone numbers can be easily spoofed. In April, Uber began requiring a valid ID in the instances when a passenger creates a new account using an untraceable payment method like a prepaid card or gift card. Lyft followed Uber’s lead in June, but only for a handful of cities, including Chicago and Atlanta. Lyft’s Adams said the company added the requirement for Minneapolis in August. Christopher Herrmann, an assistant professor at John Jay College of Criminal Justice and former crime analyst supervisor with the New York City Police Department, sees these carjackings of Uber and Lyft drivers as crimes of opportunity. “You can control the situation quite a bit,” Herrmann said, speaking from the perspective of would-be carjackers. “You’re guaranteed a nicer car. You can control the location where you get picked up. You can control what time of day it is. It’s like dial-a-carjack.” Drivers Say They’re on Their Own LaDuke first learned about Uber and Lyft drivers being carjacked in Minneapolis from a popular Twitter account called , created by volunteers who listen to police scanner audio feeds. Through those feeds, CrimeWatchMpls heard and tweeted about more than a dozen police dispatch reports of ride-hail drivers being carjacked in October. CrimeWatchMpls “Robbery of person at gunpoint. Uber driver. Loss: Vehicle, wallet phone, red Camry,” read on Oct. 4. one Twitter post Another, two weeks later, , “6:15 a.m., Lyft driver carjacked at gunpoint…. This is officially a crisis for ride share drivers in #Mpls.” read That same day, the people who run CrimeWatchMpls, who declined to comment for this story, wrote a blog post about the . “In just the last seven days (since Oct. 14), we’ve reported ten such incidents that have been aired on police dispatch. And these are just the ones we heard or know about,” read the blog post. rash of carjackings of Uber and Lyft drivers Two days later, the Minneapolis Police Department issued its citywide alert to ride-hail drivers. At that point, LaDuke said, neither Uber nor Lyft had warned Minneapolis drivers about the carjackings. On Oct. 28, nearly a week after the police alert, Uber sent drivers there a message titled “Safety tips for handling carjackings.” “Minneapolis police have reported a rise in robberies, car thefts and carjackings over the past several months,” read the message, which LaDuke shared with The Markup. The alert advises drivers to give up their vehicle and call 911 in the event of such an incident. LaDuke said he has not received any notices about the Minneapolis carjackings from Lyft. “The fact that the Minneapolis police would release this statement specific to Uber and Lyft drivers before Uber and Lyft release information had me concerned,” LaDuke said. “As a driver, we have to periodically take a selfie to show we are who we say we are, we have to have a background check. This is to keep riders safe, which is fine. But what are they doing for the drivers?” Lyft’s Adams said the company “recently sent drivers in Minneapolis emails and in-app messages highlighting safety features available to drivers and tips about staying safe on the road.” She didn’t respond to questions about whether Lyft had warned Minneapolis drivers of the carjackings specifically. Unofficial Facebook and Reddit groups where drivers in Minneapolis go to share information are filled with safety concerns. One driver in a private Facebook group said he has invested in safety gear: “1. Bullet Vest 2. Two phones 3. Dummy wallet 4. Two dash cams,” he wrote. Others say they’ve started carrying weapons, like guns and bear mace, which is prohibited by Uber and Lyft. Another driver on wrote, “I won’t pickup in North Mpls, where the majority have occurred.” Reddit According to the Minneapolis Police Department, most of the carjackings of Uber and Lyft drivers have happened in North Minneapolis, with some also occurring in Northeast and South Minneapolis. LaDuke said when he gets pinged for rides in these neighborhoods, he’s hyper-aware of his surroundings and makes sure not to stop in isolated areas or places where he could get boxed in. “It’s like I’m afraid to pick people up in that area, which is sad for me,” LaDuke said. “I grew up in North Minneapolis.” Herrmann, the assistant professor at John Jay, said most people think of their cars as a secure place and an extension of their home, so when carjackings happen, it can feel especially violating. “If someone is pointing a gun at your face and yelling at you to get out of your car, that’s a really traumatic event,” Herrmann said. “The mental scar that that leaves—every time I get in my car I think, ‘Am I going to get dragged out of my car again?’ ” Herrmann said that after carjackings a lot of people tend to change their habits, like driving less and avoiding certain areas and times of day. “The problem with gig workers is, that’s the way they make their living,” he said. “They don’t have the option or the luxury to say, ‘I’m not going to work anymore.’ ” Written by: Dara Kerr Originally published here

Many Minneapolis Uber and Lyft Drivers Were Victims of Reported Carjackings Last Fall 

Ridesharing is possibly one of the most popular and cost-effective ways for Americans to get where they need to go, and the pandemic got us hooked on delivery. The gig economy is booming, and rideshare and delivery drivers are providing a valuable service. Statistics show that calls a rideshare service like Uber at least once a month, and order takeout or delivery at least once a week. 1 in 4 Americans 60 percent of US consumers However, anyone who has decided to become a rideshare and delivery driver knows that it's not as easy as simply accepting a job and making a profit. In fact, it can be difficult for drivers to earn enough cash for their time to be worthwhile. There are a few logistical problems that make this challenging. First, some drivers operate across multiple platforms (e.g., driving for Lyft, Uber, and Doordash at the same time). Second, every minute spent going to pick up a customer is a minute with no profit. Third, not all offered jobs are viable, and drivers must spend time sorting through jobs until they find ones that will suit them. The good news is that there are tips for gig drivers to maximize profits and minimize risks and wasted time. First Things First: A Numbers Breakdown of the Gig Economy Even before the pandemic, workers were moving toward a gig economy. People need freedom and flexibility, and traditional office jobs simply don't offer these things. Remote work has indeed increased the flexibility of a conventional office setting, but the fact remains that there are still plenty of limitations on earning potential and scheduling. Currently, Gallup estimates that about of Americans leverage gig work as their primary income. In particular, many of these workers are part of the ever-growing rideshare and delivery market. 29 percent Mordor Intelligence predicts that the from $73 billion in 2020 to $209.6 billion by 2026. This is due to , including government incentives to encourage ridesharing, increased urbanization, and more ubiquitous internet and smartphone penetration. When it comes to delivery, the fastest-growing market is food delivery. It is expected to grow by between 2021 and 2026. global rideshare market will increase several factors 10.5 percent We're trending toward carpooling and ridesharing becoming the norm once again, which is something we haven't truly seen since the 1970s. This means that the number of drivers will continue to increase, and the available rideshare services may also expand. Add this to a sharp uptick in the number of customers looking for a reliable ride or prompt delivery, and there is suddenly plenty of incentive for rideshare and delivery drivers to look for ways to maximize their time. Current Challenges Faced By Drivers Let's look at the problems that prevent drivers from reaching their full earning potential. . Every minute spent driving an empty car cuts into the day's profits, so top earners understand that it's essential to minimize the amount of "empty leg" driving that happens during a shift. First, there's the problem of wasted miles . Whether drivers work for one service or multiple, it takes valuable time to sort through customers to find the most profitable orders. In addition, it's tedious and time-consuming to have to constantly manage your driving status and process orders. Second is the issue of efficiency . In an ideal world, drivers would be able to plot out the most efficient and profitable ride routes from all available rideshare and delivery apps. Doing this by hand isn't really viable because it takes too much time, and there is too much room for error. The third and final challenge is the inability to effectively map and multitask 5 Secrets For Gig Drivers to Up Their Profit Margins In the case of every rideshare or delivery app, there are a few things drivers can do to maximize their hourly intake. Filter smarter Setting up your search filters correctly can do a lot to improve your rates. By adjusting the cost per ride, and the length of ride filters properly - your cost per mile becomes optimal. These settings can be applied only when working delivery gigs with Uber Eats, Doordash, Grubhub etc. With ridesharing, whenever possible, limit your drive time to no more than 5 minutes to pick up a passenger. Even if the fee is lower, you make up for it with less empty car time. Aim for high-rated clients More experienced drivers know that it's usually best to stick with clients rated no less than 4.7 with Uber and 4.8 with Lyft. It may be difficult to find clients with high ratings in some cases, but the point is to limit your interaction with low-rated customers. Low-ranked passengers present a higher risk of losing valuable time. Some drivers also find that lower-rated customers make trips more difficult, so, you have to prioritize higher ratings. Consider adding deliveries while you drive Another secret to increased profits is playing "time Tetris," which just means scheduling your drive time as efficiently as possible. It's not always possible to perfectly fit rideshare customers into every portion of your schedule - supplement those empty times with convenient deliveries. And vice versa. It can be helpful to take some time to plan out a route and decide which apps you'll be accepting work from before you get started. You can even make a paper or digital list. Alternatively, using an automated assistant like takes away this extra planning step by handling it while you work. Muver Don't forget about vehicle upkeep One big mistake that I see many drivers make is forgetting to account for the costs of gas, cleaning, and general maintenance. These are overhead expenses that can put a big dent in your overall profits if you don't take the time to budget for them. Plan for things like regular interior detailing, oil changes, tire rotations, and roadside assistance, and use these costs to create a budget for your business. Consider letting the app handle the admin work In my experience, sorting through the available delivery and rideshare clients is the part of the job that hurts a driver's profit margins the most. Doing all of that work manually means that drivers must balance efficiency and road safety with making the most profitable use of their time. The assistant app automates tasks like accepting, completing, and managing orders for drivers. Once the driver sets initial parameters, the app uses the device's built-in accessibility services combined with deep learning technology and screen-grabbing capabilities to automatically filter and process orders while also updating a driver's status. All of this means a driver can essentially "set it and forget it" when managing rides and deliveries. The app handles all of the background administrative tasks so the driver can simply focus on safe driving and churning out orders as efficiently as possible. Let's Improve the Gig Economy with Better Rideshares and Deliveries Gig drivers deserve to have as much freedom and flexibility as possible to reach their fullest potential when making money. I believe we will see a measurable increase in the demand for ridesharing and delivery, which means that the current challenges will only be exacerbated. This is the first time in history that we've had the technology to make ridesharing a better, faster, simpler alternative to public transit or driving a personal vehicle. Between smart technology and the development of more robust, more intuitive automatization, gig drivers can make more money than ever before. The important thing for gig drivers to remember is that they must invest in themselves by learning how to manage their time and lower overhead costs. If they can do this with apps like Muver and intelligent planning, they will be able to pull in enough money to make deliveries and rideshares more than just a side hustle.

5 Secrets to Making More Money as a Gig Driver on Uber, Lyft, and More

Uber and Lyft Drivers are Increasingly Victims of Carjacking

Within a decade, Uber became the world's most valuable startup with a $78 billion valuation in 2020. But what made Uber so successful? Is it just because they offer an app that connects riders and drivers? Or is there more to it than meets the eye? This article will explore what makes Uber a by looking at three key factors: innovative solutions, stunt marketing, and profitability strategy. successful company Uber’s business model is straightforward: it matches people who need rides with drivers willing to provide them. If you think that sounds pretty much like a traditional cab company, you’re right. There is direct competition between Uber and traditional taxi services. However, unlike cabs, Uber drivers use their own car, so they must pay for all maintenance and repair costs associated with it. How It All Started The idea of Uber was born in Paris in the year of 2008. Travis Kalanick and Garret Camp were at the annual tech conference, LeWeb. After the event, they were left without transportation when standing outside in the cold, waiting for a cab. From there, an idea came.  “What if you could request a ride from your phone?” The answer to that would be a service that we would later get to know as Uber. Kalanick and Camp originally wanted their idea to be a timeshare limo service that one could access with an app. The two went their separate ways, but Camp was so fascinated by this idea and went ahead to purchase the domain name UberCab.com. The Launch of UberCab In 2009, Camp worked on a prototype for UberCab while being the CEO of StumbleUpon. In the same year’s summer, Kalanick was finally persuaded to join as the “Chief Incubator” of UberCab. UberCab was tested with only three cars in New York the following year and then officially launched in May. A Tough Year In July 2015, Uber became the most valued startup when it was valued at $51 billion after another funding round. In June 2016, Uber raised another $3.5 billion from Saudi Arabia’s Wealth Fund. However, 2017 was a very tough year for Uber. The controversies started when a female engineer called out the sexist culture in a blog post. Reportedly, Uber’s corporate culture was hostile and sexist to people. The post went viral, and it caused many people to be laid off as a result. Uber then held an internal investigation known as the “Holder Investigation.” Meanwhile, Kalanick resigned as CEO due to a shareholder revolt. In the January 2018 funding, Uber’s value was reduced from $70 billion to $48 billion. Back on the Right Track In a little over two months after Kalanick resigned, Dara Khosrowshahi was announced as the new CEO. In May 2018, a new offer was presented, valuing the company at $62 billion. In the same year, Japanese conglomerate Softbank Group and investors bid for 20% of Uber's stock during the lower valuation period. Allegedly, the deal gave Softbank 15%, and Uber got a powerful ally in Asia. The Secret to Uber’s Growth How did Uber do it all? Uber began as an idea, and from that idea, grew into a billion-dollar company that has survived adversity and scandal. Exactly what makes it so big that it spawned thousands of services based on the same concept? Innovative Solutions The design of the app and service is the most important reason why customers love Uber. You can order a ride by simply pulling out your phone and tapping a button. The GPS on your phone shows where you are. The driver also knows where you're headed since you entered the address into the app. In addition, it has your credit card information, so there is no need for a financial exchange between you and the driver. Compared to the traditional taxi industry, just think about all the steps that have been removed. For example, having to find the phone number for a taxi company was already a significant obstacle. Afterward, you would need to speak with an operator and provide your address. Then a taxi would pick you up, but you would not know exactly when it would arrive. Additionally, you would need to use a payment method by hand at the end of your ride. To provide the best service possible, every company should minimize the steps their customers must take. With its technology, Uber offers basic services of connecting people and payment-on-demand to many. This technology represents the gig economy or technology-mediated by on-demand services. Word of Mouth There is no advertising better than word of mouth. It is one of the reasons why you don’t see ads of Starbucks everywhere—word-of-mouth is more than enough to work for them. With Uber being a new startup, it encouraged its initial customers to spread the word by giving them a Referral Bonus. So their friends get their first ride free while they get credits for the referral, too. Partnership Strategy Uber calls itself a technology company and not a transportation service. Because of this, their drivers are treated as independent contractors. Accordingly, Uber's drivers are not considered key resources in Uber's internal processes but rather key partners. Uber drivers would need to pay more taxes if they were Uber employees, and as a result, it would be less profitable for them since their clients would also pay a higher price for it. Surprise and Delight When Uber introduces a new service or a major overhaul of an existing one, they often include some “gimmicks” with it. This is why they are dubbed the masters of “ .” They pull off quirky stunts like kitten delivery or the chance for passengers to get a ride with celebrity drivers. stunt marketing These tactics work well, especially in the age of social media, where a buzz can be easily generated, and something can go viral in just a few hours. Final Words Uber has grown much more quickly than traditional taxi services due mainly to its use of technology. The company’s rapid success is rooted in the fact that it was the first to develop a "disruptive" business model and took advantage of emerging technologies, such as smartphones. Also Published On: https://newsletter.roioverload.com/p/how-uber-became-the-worlds-most-valuable

Startup Stories: The 'Uber Success' of Uber 

What is the primary goal of any business? Without any doubt – money, and there is nothing wrong with that. , thus making our life easier and more comfortable. Profits allow companies to invest in R&D and bring new products and services to the market For example, we could compare a vehicle industry evolution over the past 50 years. Back in the day, a serious car accident would normally end up with someone´s death. Today, thanks to engineering genius and safety control people survive even 100 mph+ head-on collisions. The same situation can be observed in the service industry. If you have access to the internet, most surely you have heard of . In the beginning, its services included only ride-hailing but with time new services appeared, such as food delivery and scooter renting. What else can the company possibly offer? It appears to be that there is still plenty of opportunities. Uber The idea itself is not new, as back in 2014, the Leafly app was already offering cannabis deliveries. It was called "Eaze" and was located in San Francisco, where cannabis is legalized. What happened to Eaze? In 2020, news broke that Eaze was having a hard time, and to keep the company, they started employees. Uber may be looking forward to launching the delivery of cannabis to the United States . laying off Eaze even tried to go beyond the online store and third-party product delivery. Instead of just doing logistics, they wanted to sell their products through their shipping warehouses. Does it mean that Uber´s idea could bring nothing but additional costs? Not necessarily. It is important to keep in mind that Uber will not have to invest tons of money to enter new markets/states. Secondly, everyone is already aware of Uber´s existence, thus marketing expenses will not be that high (a priori). offering an unusual integration for its customers: now passengers have the opportunity to sign up for . The presentation of the new program says that any client will be able to get vaccinated at Walgreens pharmacies (a joint agreement was signed between the two companies). The company is also taking advantage of the coronavirus crisis, vaccinations An early universal vaccination means that the number of trips will increase, and therefore the company's income. Uber did not limit itself to medical topics and announced cooperation with the largest American firms (Hertz, Avis Budget Group) for car rental. Starting this week, Why are they doing it? customers will be able to book rental cars through the Uber app in the United States. . Earlier this year, Uber CEO that the company is considering accepting crypto for rides. "Just like we accept all kinds of local currency we are going to look at cryptocurrency and or bitcoin in terms of currency to transact. That's good for business, that's good for our riders and our eaters," he said. The question now is when Uber will get on the train of crypto fever said In conclusion, it looks like this . Even though, the company still doesn't look cheap in terms of ratios. At the same time, when it reports results for the quarter ended March 2021 (on May 5, 2021). company's revenues have a bright future the market expects Uber Technologies to deliver a year-over-year increase in earnings on lower revenues

When Should We Expect Uber Coin?

Eva Co-op Is Continuing The Cooperative Tradition This article is based on interviews I conducted while researching for the article " Inside the Cryptocurrency Casino " in the October issue of Current Affairs. Much of the material from that article was omitted from the final article, but after several reader enquiries, the unpublished material is presented here.  I have no relationship with the Eva Coop, financial or otherwise. Joe Biden wasn’t the only one popping champagne after last year's election. While all eyes were on the presidential race, Big Tech scored a major victory with the passage of Proposition 22, which exempts drivers in the gig economy from the protection of California’s employment laws. By all accounts, it was the most expensive ballot measure in California history. Companies like Lyft, Uber, DoorDash, Postmates and Instacart spent a combined , about ten times as much as the labor groups which opposed them. $205 million Californians were “ ,” not only on television and radio but also through their smartphones. Anyone in California who opened the Uber app in the month before the election had to sit through a pro-22 ad, warning them of higher fees and longer wait times if the proposal failed. deluged with ads mandatory Afterwards, they were prompted to click “Yes on 22” in order to use the app. (There was no option to vote no, but users could click “Okay.”) As expensive as those ads were, they were a bargain compared to what the companies saved in salaries, sick leave, training, insurance and other worker protections. For most companies in the gig economy, the road to profitability comes from cutting labor costs while passing expenses like maintenance and insurance to their drivers. Uber, for example, burned $8.5 billion last year in an effort to undercut its competitors—and once they're out of business, Uber can safely raise prices, having established an effective monopoly on local markets. The system squeezes value from both drivers and riders; fewer than of Uber drivers last a full year. four percent This business model reflects the worst aspects of venture capitalism, says Dardan Isufi, co-founder and Chief Operating Officer of the Montreal-based . Eva is a ride sharing platform, similar to Uber, but with two key distinctions. Eva Co-op First, . It is owned by the riders and drivers, who vote on key decisions, elect the company’s board, and decide how to allocate revenues. Eva is structured as a cooperative Also, unlike centralized competitors, Eva’s app is based on blockchain technology, which is used to protect the data of its users and avoid centralization around a single corporate entity. Power To The Riders "We had the idea in late 2017, when Uber was bullying the government of Quebec,” Isufi explained over Zoom last Thanksgiving weekend. The government had announced legislation requiring Uber drivers to take 35 hours of online training, the same amount of training required for taxi drivers. In response, the company threatened to leave the province. Uber ultimately did not leave Quebec, but the episode provided the idea for a new kind of ridesharing platform. Along with software engineer Raphael Gaudreault, Isufi alighted on the idea of a mobility app that serves the interests of the users. “We decided to ally the cooperative principle of management to decentralization,” Isufi said. Using blockchain-based smart contracts, the app allows Eva to “give back the means of production to workers, and also to give more power to riders.” Although it only hit the road in 2019, Eva is already going places. In Montreal and Quebec City, Eva has 850 driver-members, as well as 28,000 riders, making it the second-largest mobility app in Quebec after Uber. A second Eva Coop is expected to launch in Alberta, with a third on the way in New York. These are the first outposts of what the founders hope will become a “global empire” of member-owned cooperatives. Eva Global provides the technology and initial funding for new franchises, which act as nodes on the Eva blockchain. User data is either controlled by the cooperatives, or encrypted securely in the users’ devices. The result is an app which is designed to serve the users, not investors. While Uber charges upwards of 25 percent of each fare (and UberEats takes even more) the Eva Co-op takes only fifteen percent, a figure which can be changed by a general vote of the membership. In addition, the cooperative provides free insurance to all drivers while they are operating, through a partnership with Desjardins General Insurance. And, while Eva Global acts as a parent company, it does not have the same control as Uber’s headquarters in San Francisco. Eva Global takes a maximum of five percent of total revenues, a ceiling which is encoded by smart contract and cannot be changed without agreement from the block producers. User data is decentralized: even if Eva Global were hacked, as Uber was in 2017, it would be impossible to leak any sensitive rider information. While the app is based on forked software, you don’t need to understand the blockchain works in order to hitch a ride. There are no private keys or twelve-word mnemonics: all you need is a phone and a credit card. EOS The most complicated aspects—like wallet creation, tokens and trading—are handled entirely on the back-end. “Every month I take my car and drive as a driver, just so I can chat with the customers,” Isufi says. Most riders, he says, don’t even know what a blockchain is. New Tech, Old Ideas The emphasis on cooperation and worker ownership may seem a bit out of place, considering the predominance of libertarian and capitalistic ideas in the blockchain space. Isufi, a former officer in the Canadian Army, is hard to pin down as either a wishy liberal or a doctrinaire Marxist. “I do like the capitalist system, in the sense that it allows us to innovate,” he says. “But I don’t like giving my money to Mark Zuckerberg or Jeff Bezos. They have enough money.” “Our goal is to make profit," he added. "But profit for who? For members. Not profit for some shareholders. " Canada has a long tradition of cooperative enterprise, dating back to the 1800s. Four in ten Canadians are a member of at least one cooperative organization, and the figure rises to 70 percent in Quebec. “Most Quebec citizens, their bank is a credit union,” Isufi says. “Most of our farmers are in agricultural co-ops. Some of the biggest stores in Canada are co-ops. For us, it was the ideological thing to do.” That tradition also helped Eva arrive at its initial seed funding. Instead of going to traditional venture capitalists, Eva raised its first $810,000 CAD from government bodies and cooperatives like Mouvement Desjardins, one of the largest credit unions in Canada. These investments allowed Eva’s founders to set up their offices and start hiring drivers, without giving control to financiers. But there are disadvantages to this approach. One of them is money: most investors are not motivated by social good, and driver-owned cooperatives are not exactly a high-yield investment. “Funding is our biggest weak point,” Isufi says candidly. “It’s almost a miracle that we were able to get this funding.” The founders are now targeting more traditional investors, in exchange for equity in Eva Global. There are also tradeoffs to using blockchain technology, despite efforts to keep it user-friendly. Unlike centralized platforms, Eva Co-op cannot reset your account if you get locked out. “People forget their passwords,” Isufi admitted. “And if they forget their security answer, they’re fucked.” That’s not the end of the world, since Eva Global can still create new user accounts and recover lost funds. But the process is still a turnoff for infrequent users.  “We’re losing a lot of drivers because of that,” Isufi says. “These are some of the barriers that blockchain imposes." Delivering Through The Pandemic The COVID-19 pandemic threw another wrench in the works, shuttering businesses and halting tourism.  When I interviewed Dardan Isufi in October, Quebec was reporting a thousand cases per day, and every restaurant and bar in Montreal was closed. Even houseguests were forbidden. But the health crisis also presented an opportunity to explore a new avenue of business: instant deliveries. “What we did is create a software that can integrate any online website,” Isufi explained, which can estimate delivery times and fees. “Even Amazon Prime cannot do better than one business day, but we can do like thirty-four minutes.” There are no credit card fees or account creation: after placing an order, customers can track deliveries in real time, call the driver, and even change the destination. Moreover, unlike the 30 percent commission by UberEats, Eva Co-op only charges merchants a flat monthly fee. “Since we’ve launched that, forty percent of our market share is instant deliveries,” Isufi says, a figure which he estimates at about 2,000 deliveries per month, for 300 merchant clients.  “I think the money-maker of Eva will be instant delivery.” Can Co-ops Beat Uber? Despite the pandemic, the Eva Coop in Quebec is continuing to onboard new riders. Ironically, Isufi says, Uber has turned into one of their best marketing tools: many drivers work on both apps, and introduce their other riders to the local ride sharing co-op. The developers are also working on new functionality for the application’s users. While cryptocurrency payments are a distant goal, the priority right now is to introduce features like tipping and shared invoices, which may appeal to a mass market. While the technology is unique, Eva’s founders see the project as more than just an interesting application of blockchain technology: it’s also a strong counterpoint to the Amazons and Ubers of the tech world, which derive value at the expense of their workers. If Eva is successful, it will be a powerful demonstration that an enterprise can be both profit-oriented and socially responsible. “Every company should be community oriented,” Isufi says. “Why should we empower some already-rich people?”

Uber, Lyft, & Co. Spent $205M On Proposition 22: Here's What Men Can Do Against Such Reckless Hate

With the advancement of technology, software applications and their related services act like bridge and establish a purposeful communication between the end-user and business owner. This technology-friendly environment not only profited to end-user and business owners but also provides a great deal to the third person. It presents a flawless idea to become an entrepreneur who is liable to moulding ideas into reality. It is the bridge between students and teachers and facilitates communication with real-time help. Why we need a tutor app? The global education app market is booming day by day because parents and students are more aware of the Internet benefits, and parents want to give their children a more personalized education. A few years back, personalized education intended a tutor (a person with experience of quality teaching), who was giving tuition for the respective subjects at the student's home or his home. But now, the scenario has changed, and education is not only packed with your educational subjects. It now covers extracurricular activities like sports, painting, dance, cooking etc. too. In another way, if you have skilled professionals, you can also have the liberty to create your app or classroom sessions online via tutor/ educational app. These applications provide many educational services, and the student will get all sorts of advice they want for any subject and flourish educational business and student both. General features of tutor’s app User-friendly apps – Tutor/Student/Admin All the should be user-friendly in use. Thus, the tutor app too.
 The app consist of three segments: tutor, student, and admin. Students and tutors need to register themselves with their respective details. The student then generates a request for the tutor with their learning needs. Now request comes to the tutor app panel and accepts accordingly. on-demand apps The admin panel is responsible for the entire management of the tutor app. Admin tracks the tutor’s appointments, student requests, payments, notification, etc. This systematic way of app working makes the app user-friendly. Advance search using Geo-location Advanced search options make sure your users can schedule tutors in few clicks. So, you need to simplify your options by adopting new technologies that suit the student’s requirements with the tutor’s qualifications. Schedule booking management This feature facilitates student to schedule his/her booking as per their convenience and tutor availability. This is the best way to get more user engagement. In-App messaging facility In-app messaging is now in trend in almost every app for better communication and for sharing other information in real-time. The student will get real-time answers for their queries. They don’t need to leave the message for the reply. So, to facilitate this feature, you require a real-time server to establish directional communication between student and tutor. In-app video conference and calling option Tuitions over video calling or video conferencing are the greatest approach to rescue students when they want an immediate requirement for discussion. For this, you need to choose such APIs that facilitate smooth calling features. Cashless Transaction with in-app payments facility Now the world is moving towards cashless transactions. It simplifies the process. So the use of in-app payment is facilitating the users with a cashless payment facility. Thus, it is preferred to use different in-app payment APIs to make tutor and student payment easy. Feedback and Rating Services It is the most notable feature of an on-demand tutor mobile app. With this feature, one can easily find the best tutor after reading the reviews and experience of the tutors. Multiple Categories Tutoring for tutors must clearly mention the list of available options such as Physics tutor, Music Tutor, Mathematics Tutor, etc. So that student will easily get what he/ she wants. apps like Uber Advance Filter The advance filter option facilitates the user to find out the best result related to their queries. 3 Lessons to remember for making an app like Uber for Tutor
s Provide a quick answer for the user’s query Induce faster response to enhanced app integrity and popularity. The educational app for students should have such an approach that understands the students' study pattern, syllabus, and then respond to them as quickly as possible. You can facilitate them to click the picture of that query and send it immediately to the tutor to get an instant answer. Also, you have to include such features in your app architecture that facilitates students to live chat or video calling for instant reply. Provide tuition with convenient and suitable methods Tutors who registered themselves with the app must have proficient knowledge of the subject they choose. So that student gets the right solution with the right person. For this, you have to hire individual tutors for each subject. Also, you can include experienced tutors and can integrate group discussions, along with video conferencing. So, in this way, a tutor can teach students on-spot with the feel of the classroom. Apply advanced quiz concept that enhances knowledge Now, an interactive way of learning is more popular. Engaging students with quizzes and tests on a regular basis enhance their knowledge and learning capacity. Thus, you should include these advanced features into your educational tutor app. Bottom lines In this blog, I have mentioned all the possible features that you need to include to . But still, it is required to do your own study to add the more enhanced features in your app. No matter what type of education app you create, it is crucial that it shares a better learning experience. So, if you want to develop a tutoring app, go with the leading app development company with sufficient experience in developing an app like Uber for the tutors. create a tutoring mobile app

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