How a single mom of four switched careers to land a six-figure salary

After separating from her husband in June, single mom Shannon Lance found herself suddenly needing to earn enough to support four children. Lance began her job search after completing an intensive 14-week program with Washington-based Coding Dojo. Just six days after beginning her job hunt, Lance secured a six-figure offer from travel expenses firm SAP Concur. “I was (previously) a teacher and had a bunch of professional experience that gave me soft skills which helped land the job,” she said. H


After separating from her husband in June, single mom Shannon Lance found herself suddenly needing to earn enough to support four children. Lance began her job search after completing an intensive 14-week program with Washington-based Coding Dojo. Just six days after beginning her job hunt, Lance secured a six-figure offer from travel expenses firm SAP Concur. “I was (previously) a teacher and had a bunch of professional experience that gave me soft skills which helped land the job,” she said. H
How a single mom of four switched careers to land a six-figure salary Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-07-10  Authors: chloe taylor
Keywords: news, cnbc, companies, learning, switched, experience, program, single, work, salary, mom, coding, land, careers, job, didnt, career, lance, sixfigure


How a single mom of four switched careers to land a six-figure salary

After separating from her husband in June, single mom Shannon Lance found herself suddenly needing to earn enough to support four children. “I have a teaching degree but (teaching) won’t pay the bills for a family of five – it’s just not an option,” she told CNBC. “I thought about nursing, but the biggest drawback was that it required going back to school for two years to get another degree – I didn’t have two years, I have kids and bills to pay.” Despite being a self-confessed technophobe, Lance decided to learn computer coding after a suggestion from her brother-in-law, taking the plunge into an entirely new career path. Lance began her job search after completing an intensive 14-week program with Washington-based Coding Dojo. Just six days after beginning her job hunt, Lance secured a six-figure offer from travel expenses firm SAP Concur. In an interview with CNBC, she shared her tips on achieving success in a new career.

Value your ‘soft skills’

Although a career change can set you back in terms of direct industry experience, Lance urged others not to underestimate the value of basic core capabilities that appeal to employers — like strong communication or leadership skills. “I was (previously) a teacher and had a bunch of professional experience that gave me soft skills which helped land the job,” she said. “(That was) combined with having just coming out of a great program which gave me all the right tech skills.”

Be willing to learn

As well as considering how your skillset could be transferred to a new industry, Lance told CNBC that having the right attitude was a real asset when it came to landing a job with no direct experience. She said she was upfront about what she could and couldn’t do, taking the approach: “I don’t know a lot about it, but I do know a little bit – and I’m willing to learn more.” According to Lance, embracing those knowledge gaps and showcasing a desire for self-improvement could be just as valuable as experience to some employers. “For the job I got, the company was starting a new team that would be using new technology, so we’d all be learning whether they hired somebody with experience or not,” she said. “They wanted people who were capable of learning quickly and who could work and learn under pressure. Going through Coding Dojo proved I had those capabilities and that desire to keep learning.”

Work your own way

Although Lance didn’t feel intellectually limited while learning to code, she said comparing her own pace of work to others’ sometimes led to unnecessary frustration and could impact her confidence. “One challenge was the amount of time it took to get through everything. I don’t think I had trouble with the actual program, but I didn’t have any tech background, so every assignment would take me one and a half times as long as everyone else,” she told CNBC. “Some of the people in my group had played on computers since they were 12 — so the assignments only took 20 to 30 minutes for them to complete.” She said it was important to find your own way to get work done, rather than sticking to the chronological or seemingly “correct” method. Her coding program was organized into three sections, and when she initially attempted to do each assignment in order, Lance found herself falling behind. “I’d have to skip forward and go back again – that’s not a good strategy,” she said. Instead, she got through all of the reading and learning materials for each topic before attempting to complete an assignment. “Make sure you do the reading and homework way before you start struggling with (graded assignments and technical work),” she said. “And make sure you allow yourself enough time outside of class to get stuff done.” Lance also advised those considering a career change not to overestimate their own academic ability. “I was pretty good in school and didn’t have to study a lot,” she said. “I went into Coding Dojo thinking I could get it done quicker, underestimating how much time it would consume. (You have to let it) take as long as it takes.”

Seek support to switch career


Company: cnbc, Activity: cnbc, Date: 2019-07-10  Authors: chloe taylor
Keywords: news, cnbc, companies, learning, switched, experience, program, single, work, salary, mom, coding, land, careers, job, didnt, career, lance, sixfigure


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Warren Buffett and Bill Gates say this is the best business book ever

When you stop paying attention to the evolving changes of society and human needs, you fall behind and become vulnerable to competitors. While writing the story, Brooks said a marketing manager told him it was the customers who were at fault. Never underestimate the importance of company culture and values. This is a powerful lesson for anyone — whether you’re a founder, manager, employee or job seeker. Having good company culture will likely lead to higher productivity and motivation, fewer emp


When you stop paying attention to the evolving changes of society and human needs, you fall behind and become vulnerable to competitors. While writing the story, Brooks said a marketing manager told him it was the customers who were at fault. Never underestimate the importance of company culture and values. This is a powerful lesson for anyone — whether you’re a founder, manager, employee or job seeker. Having good company culture will likely lead to higher productivity and motivation, fewer emp
Warren Buffett and Bill Gates say this is the best business book ever Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: david neagle, getty images
Keywords: news, cnbc, companies, gates, bill, manager, say, wilson, youre, book, business, marketing, job, learning, important, wouldnt, company, warren, culture, buffett, best


Warren Buffett and Bill Gates say this is the best business book ever

Here’s how to get a job at Goldman Sachs 9:32 AM ET Thu, 4 April 2019 | 04:32

Ford was dissatisfied with the poll results and ended up going its own way. Eager to create hype, it began marketing the car one year before it was even completed. And on launch day, the model was delivered with oil leaks and trunks that wouldn’t open. It was also mocked as being too expensive and using up too much gas.

When you stop paying attention to the evolving changes of society and human needs, you fall behind and become vulnerable to competitors.

2. Failure isn’t a bad thing — accept it, learn from it, and move on from it.

The big Edsel flop led to a $350 million loss. And yet, Ford’s executives took zero responsibility for their failures. In fact, they claimed to have done everything right.

While writing the story, Brooks said a marketing manager told him it was the customers who were at fault. “What they’d been buying for several years encouraged the industry to build exactly this kind of car,” the representative said. “We gave it to them, and they wouldn’t take it. Well, they shouldn’t have acted like that. And now the public wants these little beetles. I don’t get it!”

People often think, If I fail, I will lose something very important — like getting into a good college, working at (or starting) a great company, getting a promotion, making lots of money and so on. But learning from our mistakes is one of the greatest tools for learning; it gives us information on what we need to do differently to succeed in life.

3. Never underestimate the importance of company culture and values.

This is a powerful lesson for anyone — whether you’re a founder, manager, employee or job seeker.

Brooks describes Xerox founder Joseph C. Wilson as being ahead of his time in the ’60s because of how he prioritized building a compassionate work culture. He made it his duty to donate millions of dollars to charities and universities. He implemented progressive hiring policies during the civil rights movement.

“To set high goals, to have almost unattainable aspirations, to imbue people with the belief that they can be achieved…these are as important as the balance sheet, perhaps more so,” Wilson said once according to Brooks.

Today, more than ever, employees value unity and purpose in a company — and they’re not afraid to quit or reject a job offer from a company with a bad reputation. Having good company culture will likely lead to higher productivity and motivation, fewer employee health issues and less turnover.

Keep this in mind as well if you’re a job seeker. Joining a company with poor culture won’t keep you happy in the long run.


Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: david neagle, getty images
Keywords: news, cnbc, companies, gates, bill, manager, say, wilson, youre, book, business, marketing, job, learning, important, wouldnt, company, warren, culture, buffett, best


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Here’s Jeff Bezos’ annual shareholder letter

Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits. You can read the letter in full below:To our shareowners:Something strange and remarkable has happened over the last 20 years. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run


Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits. You can read the letter in full below:To our shareowners:Something strange and remarkable has happened over the last 20 years. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run
Here’s Jeff Bezos’ annual shareholder letter Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: todd haselton, alex wong, getty images news, getty images
Keywords: news, cnbc, companies, letter, way, amazon, bezos, employees, shareholder, heres, aws, wandering, learning, alexa, customers, jeff, business, sellers, annual


Here's Jeff Bezos' annual shareholder letter

Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits.

Bezos also warned that because Amazon has such a massive size and scale, shareholders can expect “multibillion-dollar failures” as the company experiments with new initiatives.

You can read the letter in full below:

To our shareowners:

Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:

1999 3% 2000 3% 2001 6% 2002 17% 2003 22% 2004 25% 2005 28% 2006 28% 2007 29% 2008 30% 2009 31% 2010 34% 2011 38% 2012 42% 2013 46% 2014 49% 2015 51% 2016 54% 2017 56% 2018 58%

The percentages represent the share of physical gross merchandise sales sold on Amazon by independent third-party sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first party sales. Third-party sales have grown from 3% of the total to 58%. To put it bluntly:

Third-party sellers are kicking our first party butt. Badly.

And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion.

Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer:

We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them. We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations. We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.

Intuition, curiosity, and the power of wandering

From very early on in Amazon’s life, we knew we wanted to create a culture of builders – people who are curious, explorers. They like to invent. Even when they’re experts, they are “fresh” with a beginner’s mind. They see the way we do things as just the way we do things now. A builder’s mentality helps us approach big, hard-to-solve opportunities with a humble conviction that success can come through iteration: invent, launch, reinvent, relaunch, start over, rinse, repeat, again and again. They know the path to success is anything but straight.

Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.

AWS’s millions of customers range from startups to large enterprises, government entities to nonprofits, each looking to build better solutions for their end users. We spend a lot of time thinking about what those organizations want and what the people inside them – developers, dev managers, ops managers, CIOs, chief digital officers, chief information security officers, etc. – want.

Much of what we build at AWS is based on listening to customers. It’s critical to ask customers what they want, listen carefully to their answers, and figure out a plan to provide it thoughtfully and quickly (speed matters in business!). No business could thrive without that kind of customer obsession. But it’s also not enough. The biggest needle movers will be things that customers don’t know to ask for. We must invent on their behalf. We have to tap into our own inner imagination about what’s possible.

AWS itself – as a whole – is an example. No one asked for AWS. No one. Turns out the world was in fact ready and hungry for an offering like AWS but didn’t know it. We had a hunch, followed our curiosity, took the necessary financial risks, and began building – reworking, experimenting, and iterating countless times as we proceeded.

Within AWS, that same pattern has recurred many times. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And on the listening-carefully-to-customers side, we heard loudly that companies felt constrained by their commercial database options and had been unhappy with their database providers for decades – these offerings are expensive, proprietary, have high-lock-in and punitive licensing terms. We spent several years building our own database engine, Amazon Aurora, a fully-managed MySQL and PostgreSQL-compatible service with the same or better durability and availability as the commercial engines, but at one-tenth of the cost. We were not surprised when this worked.

But we’re also optimistic about specialized databases for specialized workloads. Over the past 20 to 30 years, companies ran most of their workloads using relational databases. The broad familiarity with relational databases among developers made this technology the go-to even when it wasn’t ideal. Though sub-optimal, the data set sizes were often small enough and the acceptable query latencies long enough that you could make it work. But today, many applications are storing very large amounts of data – terabytes and petabytes. And the requirements for apps have changed. Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second. It’s not just key-value stores like DynamoDB, but also in-memory databases like Amazon ElastiCache, time series databases like Amazon Timestream, and ledger solutions like Amazon Quantum Ledger Database – the right tool for the right job saves money and gets your product to market faster.

We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run rate business and growing fast.

Imagining the impossible

Amazon today remains a small player in global retail. We represent a low single-digit percentage of the retail market, and there are much larger retailers in every country where we operate. And that’s largely because nearly 90% of retail remains offline, in brick and mortar stores. For many years, we considered how we might serve customers in physical stores, but felt we needed first to invent something that would really delight customers in that environment. With Amazon Go, we had a clear vision. Get rid of the worst thing about physical retail: checkout lines. No one likes to wait in line. Instead, we imagined a store where you could walk in, pick up what you wanted, and leave.

Getting there was hard. Technically hard. It required the efforts of hundreds of smart, dedicated computer scientists and engineers around the world. We had to design and build our own proprietary cameras and shelves and invent new computer vision algorithms, including the ability to stitch together imagery from hundreds of cooperating cameras. And we had to do it in a way where the technology worked so well that it simply receded into the background, invisible. The reward has been the response from customers, who’ve described the experience of shopping at Amazon Go as “magical.” We now have 10 stores in Chicago, San Francisco, and Seattle, and are excited about the future.

Failure needs to scale too

As a company grows, everything needs to scale, including the size of your failed experiments. If the size of your failures isn’t growing, you’re not going to be inventing at a size that can actually move the needle. Amazon will be experimenting at the right scale for a company of our size if we occasionally have multibillion-dollar failures. Of course, we won’t undertake such experiments cavalierly. We will work hard to make them good bets, but not all good bets will ultimately pay out. This kind of large-scale risk taking is part of the service we as a large company can provide to our customers and to society. The good news for shareowners is that a single big winning bet can more than cover the cost of many losers.

Development of the Fire phone and Echo was started around the same time. While the Fire phone was a failure, we were able to take our learnings (as well as the developers) and accelerate our efforts building Echo and Alexa. The vision for Echo and Alexa was inspired by the Star Trek computer. The idea also had origins in two other arenas where we’d been building and wandering for years: machine learning and the cloud. From Amazon’s early days, machine learning was an essential part of our product recommendations, and AWS gave us a front row seat to the capabilities of the cloud. After many years of development, Echo debuted in 2014, powered by Alexa, who lives in the AWS cloud.

No customer was asking for Echo. This was definitely us wandering. Market research doesn’t help. If you had gone to a customer in 2013 and said “Would you like a black, always-on cylinder in your kitchen about the size of a Pringles can that you can talk to and ask questions, that also turns on your lights and plays music?” I guarantee you they’d have looked at you strangely and said “No, thank you.”

Since that first-generation Echo, customers have purchased more than 100 million Alexa-enabled devices. Last year, we improved Alexa’s ability to understand requests and answer questions by more than 20%, while adding billions of facts to make Alexa more knowledgeable than ever. Developers doubled the number of Alexa skills to over 80,000, and customers spoke to Alexa tens of billions more times in 2018 compared to 2017. The number of devices with Alexa built-in more than doubled in 2018. There are now more than 150 different products available with Alexa built-in, from headphones and PCs to cars and smart home devices. Much more to come!

One last thing before closing. As I said in the first shareholder letter more than 20 years ago, our focus is on hiring and retaining versatile and talented employees who can think like owners. Achieving that requires investing in our employees, and, as with so many other things at Amazon, we use not just analysis but also intuition and heart to find our way forward.

Last year, we raised our minimum wage to $15-an-hour for all full-time, part-time, temporary, and seasonal employees across the U.S. This wage hike benefitted more than 250,000 Amazon employees, as well as over 100,000 seasonal employees who worked at Amazon sites across the country last holiday. We strongly believe that this will benefit our business as we invest in our employees. But that is not what drove the decision. We had always offered competitive wages. But we decided it was time to lead – to offer wages that went beyond competitive. We did it because it seemed like the right thing to do.

Today I challenge our top retail competitors (you know who you are!) to match our employee benefits and our $15 minimum wage. Do it! Better yet, go to $16 and throw the gauntlet back at us. It’s a kind of competition that will benefit everyone.

Many of the other programs we have introduced for our employees came as much from the heart as the head. I’ve mentioned before the Career Choice program, which pays up to 95% of tuition and fees towards a certificate or diploma in qualified fields of study, leading to in-demand careers for our associates, even if those careers take them away from Amazon. More than 16,000 employees have now taken advantage of the program, which continues to grow. Similarly, our Career Skills program trains hourly associates in critical job skills like resume writing, how to communicate effectively, and computer basics. In October of last year, in continuation of these commitments, we signed the President’s Pledge to America’s Workers and announced we will be upskilling 50,000 U.S. employees through our range of innovative training programs.

Our investments are not limited to our current employees or even to the present. To train tomorrow’s workforce, we have pledged $50 million, including through our recently announced Amazon Future Engineer program, to support STEM and CS education around the country for elementary, high school, and university students, with a particular focus on attracting more girls and minorities to these professions. We also continue to take advantage of the incredible talents of our veterans. We are well on our way to meeting our pledge to hire 25,000 veterans and military spouses by 2021. And through the Amazon Technical Veterans Apprenticeship program, we are providing veterans on-the-job training in fields like cloud computing.

A huge thank you to our customers for allowing us to serve you while always challenging us to do even better, to our shareowners for your continuing support, and to all our employees worldwide for your hard work and pioneering spirit. Teams all across Amazon are listening to customers and wandering on their behalf!

As always, I attach a copy of our original 1997 letter. It remains Day 1.

Sincerely,

Jeffrey P. Bezos

Founder and Chief Executive Officer

Amazon.com, Inc.


Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: todd haselton, alex wong, getty images news, getty images
Keywords: news, cnbc, companies, letter, way, amazon, bezos, employees, shareholder, heres, aws, wandering, learning, alexa, customers, jeff, business, sellers, annual


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Here’s Jeff Bezos’ annual shareholder letter

Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits. You can read the letter in full below:To our shareowners:Something strange and remarkable has happened over the last 20 years. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run


Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits. You can read the letter in full below:To our shareowners:Something strange and remarkable has happened over the last 20 years. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run
Here’s Jeff Bezos’ annual shareholder letter Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: todd haselton, alex wong, getty images news, getty images
Keywords: news, cnbc, companies, letter, way, amazon, bezos, employees, shareholder, heres, aws, wandering, learning, alexa, customers, jeff, business, sellers, annual


Here's Jeff Bezos' annual shareholder letter

Jeff Bezos on Thursday published Amazon’s annual shareholder letter, in which he called on rivals to match Amazon’s pay and benefits.

Bezos also warned that because Amazon has such a massive size and scale, shareholders can expect “multibillion-dollar failures” as the company experiments with new initiatives.

You can read the letter in full below:

To our shareowners:

Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:

1999 3% 2000 3% 2001 6% 2002 17% 2003 22% 2004 25% 2005 28% 2006 28% 2007 29% 2008 30% 2009 31% 2010 34% 2011 38% 2012 42% 2013 46% 2014 49% 2015 51% 2016 54% 2017 56% 2018 58%

The percentages represent the share of physical gross merchandise sales sold on Amazon by independent third-party sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first party sales. Third-party sales have grown from 3% of the total to 58%. To put it bluntly:

Third-party sellers are kicking our first party butt. Badly.

And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion.

Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer:

We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them. We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations. We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.

Intuition, curiosity, and the power of wandering

From very early on in Amazon’s life, we knew we wanted to create a culture of builders – people who are curious, explorers. They like to invent. Even when they’re experts, they are “fresh” with a beginner’s mind. They see the way we do things as just the way we do things now. A builder’s mentality helps us approach big, hard-to-solve opportunities with a humble conviction that success can come through iteration: invent, launch, reinvent, relaunch, start over, rinse, repeat, again and again. They know the path to success is anything but straight.

Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.

AWS’s millions of customers range from startups to large enterprises, government entities to nonprofits, each looking to build better solutions for their end users. We spend a lot of time thinking about what those organizations want and what the people inside them – developers, dev managers, ops managers, CIOs, chief digital officers, chief information security officers, etc. – want.

Much of what we build at AWS is based on listening to customers. It’s critical to ask customers what they want, listen carefully to their answers, and figure out a plan to provide it thoughtfully and quickly (speed matters in business!). No business could thrive without that kind of customer obsession. But it’s also not enough. The biggest needle movers will be things that customers don’t know to ask for. We must invent on their behalf. We have to tap into our own inner imagination about what’s possible.

AWS itself – as a whole – is an example. No one asked for AWS. No one. Turns out the world was in fact ready and hungry for an offering like AWS but didn’t know it. We had a hunch, followed our curiosity, took the necessary financial risks, and began building – reworking, experimenting, and iterating countless times as we proceeded.

Within AWS, that same pattern has recurred many times. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And on the listening-carefully-to-customers side, we heard loudly that companies felt constrained by their commercial database options and had been unhappy with their database providers for decades – these offerings are expensive, proprietary, have high-lock-in and punitive licensing terms. We spent several years building our own database engine, Amazon Aurora, a fully-managed MySQL and PostgreSQL-compatible service with the same or better durability and availability as the commercial engines, but at one-tenth of the cost. We were not surprised when this worked.

But we’re also optimistic about specialized databases for specialized workloads. Over the past 20 to 30 years, companies ran most of their workloads using relational databases. The broad familiarity with relational databases among developers made this technology the go-to even when it wasn’t ideal. Though sub-optimal, the data set sizes were often small enough and the acceptable query latencies long enough that you could make it work. But today, many applications are storing very large amounts of data – terabytes and petabytes. And the requirements for apps have changed. Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second. It’s not just key-value stores like DynamoDB, but also in-memory databases like Amazon ElastiCache, time series databases like Amazon Timestream, and ledger solutions like Amazon Quantum Ledger Database – the right tool for the right job saves money and gets your product to market faster.

We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run rate business and growing fast.

Imagining the impossible

Amazon today remains a small player in global retail. We represent a low single-digit percentage of the retail market, and there are much larger retailers in every country where we operate. And that’s largely because nearly 90% of retail remains offline, in brick and mortar stores. For many years, we considered how we might serve customers in physical stores, but felt we needed first to invent something that would really delight customers in that environment. With Amazon Go, we had a clear vision. Get rid of the worst thing about physical retail: checkout lines. No one likes to wait in line. Instead, we imagined a store where you could walk in, pick up what you wanted, and leave.

Getting there was hard. Technically hard. It required the efforts of hundreds of smart, dedicated computer scientists and engineers around the world. We had to design and build our own proprietary cameras and shelves and invent new computer vision algorithms, including the ability to stitch together imagery from hundreds of cooperating cameras. And we had to do it in a way where the technology worked so well that it simply receded into the background, invisible. The reward has been the response from customers, who’ve described the experience of shopping at Amazon Go as “magical.” We now have 10 stores in Chicago, San Francisco, and Seattle, and are excited about the future.

Failure needs to scale too

As a company grows, everything needs to scale, including the size of your failed experiments. If the size of your failures isn’t growing, you’re not going to be inventing at a size that can actually move the needle. Amazon will be experimenting at the right scale for a company of our size if we occasionally have multibillion-dollar failures. Of course, we won’t undertake such experiments cavalierly. We will work hard to make them good bets, but not all good bets will ultimately pay out. This kind of large-scale risk taking is part of the service we as a large company can provide to our customers and to society. The good news for shareowners is that a single big winning bet can more than cover the cost of many losers.

Development of the Fire phone and Echo was started around the same time. While the Fire phone was a failure, we were able to take our learnings (as well as the developers) and accelerate our efforts building Echo and Alexa. The vision for Echo and Alexa was inspired by the Star Trek computer. The idea also had origins in two other arenas where we’d been building and wandering for years: machine learning and the cloud. From Amazon’s early days, machine learning was an essential part of our product recommendations, and AWS gave us a front row seat to the capabilities of the cloud. After many years of development, Echo debuted in 2014, powered by Alexa, who lives in the AWS cloud.

No customer was asking for Echo. This was definitely us wandering. Market research doesn’t help. If you had gone to a customer in 2013 and said “Would you like a black, always-on cylinder in your kitchen about the size of a Pringles can that you can talk to and ask questions, that also turns on your lights and plays music?” I guarantee you they’d have looked at you strangely and said “No, thank you.”

Since that first-generation Echo, customers have purchased more than 100 million Alexa-enabled devices. Last year, we improved Alexa’s ability to understand requests and answer questions by more than 20%, while adding billions of facts to make Alexa more knowledgeable than ever. Developers doubled the number of Alexa skills to over 80,000, and customers spoke to Alexa tens of billions more times in 2018 compared to 2017. The number of devices with Alexa built-in more than doubled in 2018. There are now more than 150 different products available with Alexa built-in, from headphones and PCs to cars and smart home devices. Much more to come!

One last thing before closing. As I said in the first shareholder letter more than 20 years ago, our focus is on hiring and retaining versatile and talented employees who can think like owners. Achieving that requires investing in our employees, and, as with so many other things at Amazon, we use not just analysis but also intuition and heart to find our way forward.

Last year, we raised our minimum wage to $15-an-hour for all full-time, part-time, temporary, and seasonal employees across the U.S. This wage hike benefitted more than 250,000 Amazon employees, as well as over 100,000 seasonal employees who worked at Amazon sites across the country last holiday. We strongly believe that this will benefit our business as we invest in our employees. But that is not what drove the decision. We had always offered competitive wages. But we decided it was time to lead – to offer wages that went beyond competitive. We did it because it seemed like the right thing to do.

Today I challenge our top retail competitors (you know who you are!) to match our employee benefits and our $15 minimum wage. Do it! Better yet, go to $16 and throw the gauntlet back at us. It’s a kind of competition that will benefit everyone.

Many of the other programs we have introduced for our employees came as much from the heart as the head. I’ve mentioned before the Career Choice program, which pays up to 95% of tuition and fees towards a certificate or diploma in qualified fields of study, leading to in-demand careers for our associates, even if those careers take them away from Amazon. More than 16,000 employees have now taken advantage of the program, which continues to grow. Similarly, our Career Skills program trains hourly associates in critical job skills like resume writing, how to communicate effectively, and computer basics. In October of last year, in continuation of these commitments, we signed the President’s Pledge to America’s Workers and announced we will be upskilling 50,000 U.S. employees through our range of innovative training programs.

Our investments are not limited to our current employees or even to the present. To train tomorrow’s workforce, we have pledged $50 million, including through our recently announced Amazon Future Engineer program, to support STEM and CS education around the country for elementary, high school, and university students, with a particular focus on attracting more girls and minorities to these professions. We also continue to take advantage of the incredible talents of our veterans. We are well on our way to meeting our pledge to hire 25,000 veterans and military spouses by 2021. And through the Amazon Technical Veterans Apprenticeship program, we are providing veterans on-the-job training in fields like cloud computing.

A huge thank you to our customers for allowing us to serve you while always challenging us to do even better, to our shareowners for your continuing support, and to all our employees worldwide for your hard work and pioneering spirit. Teams all across Amazon are listening to customers and wandering on their behalf!

As always, I attach a copy of our original 1997 letter. It remains Day 1.

Sincerely,

Jeffrey P. Bezos

Founder and Chief Executive Officer

Amazon.com, Inc.


Company: cnbc, Activity: cnbc, Date: 2019-04-11  Authors: todd haselton, alex wong, getty images news, getty images
Keywords: news, cnbc, companies, letter, way, amazon, bezos, employees, shareholder, heres, aws, wandering, learning, alexa, customers, jeff, business, sellers, annual


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How to win at grown-up life while you’re still learning to grow up

“While I have the things I need and am a success with my budgeting, my financial life is also a very hard struggle to balance,” Carroll said. It seemed to be in great shape, but she found out after purchasing it that it needed a new furnace. Carroll’s social life has taken a hit because of her tight work and school schedule. “There is no way that I would be able to do any of the choices I have made without them,” Carroll said. Learning the field has helped her to look at ads differently and broa


“While I have the things I need and am a success with my budgeting, my financial life is also a very hard struggle to balance,” Carroll said. It seemed to be in great shape, but she found out after purchasing it that it needed a new furnace. Carroll’s social life has taken a hit because of her tight work and school schedule. “There is no way that I would be able to do any of the choices I have made without them,” Carroll said. Learning the field has helped her to look at ads differently and broa
How to win at grown-up life while you’re still learning to grow up Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-04-08  Authors: jill cornfield, source, jessica carroll, -lisa chastain, millennial money coach
Keywords: news, cnbc, companies, debt, grownup, yougot, emergency, willing, great, life, carroll, things, learning, support, grow, youre, win, financial


How to win at grown-up life while you're still learning to grow up

Jessica Carroll, 22, splits her time between college and two part-time jobs. Neither pays benefits. “While I have the things I need and am a success with my budgeting, my financial life is also a very hard struggle to balance,” Carroll said.

On a starting salary, a single emergency can wreak financial havoc. Carroll, who lives in Garrett, Indiana, bought a house for $56,000. It seemed to be in great shape, but she found out after purchasing it that it needed a new furnace. That same week, a tree fell on her car, totaling it. Together, these occurrences emptied her emergency fund.

Carroll’s social life has taken a hit because of her tight work and school schedule. “It is not easy by any means,” she said.

More from Invest in You:

Got goals? Simple actions to help get you things you want

Do this now to feel financially secure in future

Friends don’t let friends stay clueless about money

Chastain names three tasks to master in your 20s: Find your own comfort level with debt, “what are you willing and not willing to go into debt for”; understand your earning potential; and choose the right people. “It’s important to have loving relationships and people that support you,” she said.

Carroll says her parents are great role models who taught her good financial habits, as well as being generous with support and even some occasional elbow grease. “There is no way that I would be able to do any of the choices I have made without them,” Carroll said.

A certain amount of luck is helpful. A bank internship turned out to be a blessing. Carroll applied to be a teller and was offered the marketing position, which she loves. Learning the field has helped her to look at ads differently and broadened her perspective.


Company: cnbc, Activity: cnbc, Date: 2019-04-08  Authors: jill cornfield, source, jessica carroll, -lisa chastain, millennial money coach
Keywords: news, cnbc, companies, debt, grownup, yougot, emergency, willing, great, life, carroll, things, learning, support, grow, youre, win, financial


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Boeing CEO says company is ‘humbled and learning’ from deadly Ethiopian Airlines crash

Boeing CEO Dennis Muilenburg said the aircraft maker was “humbled and learning” from an Ethiopian Airlines crash that killed 157 people earlier this month, the second fatal crash of its popular 737 Max plane in less than 5 months. “We’ve stood shoulder to shoulder in partnership with the Ethiopian team to grieve and extend our deepest sympathies to the families, friends and communities of the passengers and crew,” Muilenburg wrote in a statement released Monday. Ethiopian Airlines said on Monday


Boeing CEO Dennis Muilenburg said the aircraft maker was “humbled and learning” from an Ethiopian Airlines crash that killed 157 people earlier this month, the second fatal crash of its popular 737 Max plane in less than 5 months. “We’ve stood shoulder to shoulder in partnership with the Ethiopian team to grieve and extend our deepest sympathies to the families, friends and communities of the passengers and crew,” Muilenburg wrote in a statement released Monday. Ethiopian Airlines said on Monday
Boeing CEO says company is ‘humbled and learning’ from deadly Ethiopian Airlines crash Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-03-26  Authors: emma newburger, stephen brashear, getty images
Keywords: news, cnbc, companies, boeing, airlines, max, statement, plane, shoulder, crash, learning, ceo, model, maker, humbled, muilenburg, ethiopian, company, killed, deadly


Boeing CEO says company is 'humbled and learning' from deadly Ethiopian Airlines crash

Boeing CEO Dennis Muilenburg said the aircraft maker was “humbled and learning” from an Ethiopian Airlines crash that killed 157 people earlier this month, the second fatal crash of its popular 737 Max plane in less than 5 months.

“We’ve stood shoulder to shoulder in partnership with the Ethiopian team to grieve and extend our deepest sympathies to the families, friends and communities of the passengers and crew,” Muilenburg wrote in a statement released Monday.

Ethiopian Airlines said on Monday it would maintain ties with the U.S. plane maker despite questions and an investigation into its 737 Max 8 model, which was also involved in the Lion Air crash that killed 189 people in October.

Boeing is under intense scrutiny as federal investigators look into whether the plane maker provided incomplete or misleading information about the model to U.S. air-safety regulators.

Read Muilenburg’s full statement below.


Company: cnbc, Activity: cnbc, Date: 2019-03-26  Authors: emma newburger, stephen brashear, getty images
Keywords: news, cnbc, companies, boeing, airlines, max, statement, plane, shoulder, crash, learning, ceo, model, maker, humbled, muilenburg, ethiopian, company, killed, deadly


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David and Claudia Harding Foundation give Cambridge University £100 million gift to support students

Other philanthropists and alumni have been known to donate large sums of money to British universities, including Bill and Melinda Gates, whose foundation donated $210 million and set up a scholarship program at Cambridge University back in 2000. The Winton Group founder graduated from Cambridge in the 1980s, with a First Class Honours degree in natural sciences that specialized in theoretical physics. David went onto establish the investment management firm in 1997, while Claudia is the Managin


Other philanthropists and alumni have been known to donate large sums of money to British universities, including Bill and Melinda Gates, whose foundation donated $210 million and set up a scholarship program at Cambridge University back in 2000. The Winton Group founder graduated from Cambridge in the 1980s, with a First Class Honours degree in natural sciences that specialized in theoretical physics. David went onto establish the investment management firm in 1997, while Claudia is the Managin
David and Claudia Harding Foundation give Cambridge University £100 million gift to support students Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-02-06  Authors: alexandra gibbs, tolga akmen, afp, getty images, courtesy, credit, university of cambridge
Keywords: news, cnbc, companies, support, gift, cambridge, david, help, students, claudia, harding, learning, million, including, university, foundation, statement


David and Claudia Harding Foundation give Cambridge University £100 million gift to support students

In a statement accompanying the announcement, Cambridge University’s Vice-Chancellor Stephen J Toope said Tuesday that the donation would be “invaluable in sustaining Cambridge’s place” among the world’s top educational institutions and help attract and support students.

“We are determined that Cambridge should nurture the finest academic talent, whatever the background or means of our students, to help us fulfil our mission ‘to contribute to society through the pursuit of education, learning and research at the highest international levels of excellence’,” he added.

David and Claudia Harding are considered “generous supporters” by the institution, with the pair having previously donated to a range of scientific and educational causes at the university, in addition to other initiatives around the U.K., including the Science Museum Group.

Other philanthropists and alumni have been known to donate large sums of money to British universities, including Bill and Melinda Gates, whose foundation donated $210 million and set up a scholarship program at Cambridge University back in 2000.

The Winton Group founder graduated from Cambridge in the 1980s, with a First Class Honours degree in natural sciences that specialized in theoretical physics. David went onto establish the investment management firm in 1997, while Claudia is the Managing Trustee of the David and Claudia Harding Foundation.

The couple said that they hoped this donation would encourage future generations of students from around the globe to study at the leading university.

“Cambridge and other British centres of learning have down the ages contributed greatly to improvements in the human condition and can continue in future to address humanity’s great challenges,” David Harding said in a statement.


Company: cnbc, Activity: cnbc, Date: 2019-02-06  Authors: alexandra gibbs, tolga akmen, afp, getty images, courtesy, credit, university of cambridge
Keywords: news, cnbc, companies, support, gift, cambridge, david, help, students, claudia, harding, learning, million, including, university, foundation, statement


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Apple’s dismissal of 200 self-driving car employees points to a shift in its AI strategy

So it came as a surprise Wednesday when CNBC learned that Apple was removing 200 employees from its self-driving car unit. Self-driving car technology may still be an important initiative at Apple. Apple’s self-driving car project, called Titan internally, started out with the desire to create an Apple-branded electric car, The Wall Street Journal reported in 2015. And just last month, Giannandrea was promoted to Apple’s executive team as vice president of machine learning and artificial intelli


So it came as a surprise Wednesday when CNBC learned that Apple was removing 200 employees from its self-driving car unit. Self-driving car technology may still be an important initiative at Apple. Apple’s self-driving car project, called Titan internally, started out with the desire to create an Apple-branded electric car, The Wall Street Journal reported in 2015. And just last month, Giannandrea was promoted to Apple’s executive team as vice president of machine learning and artificial intelli
Apple’s dismissal of 200 self-driving car employees points to a shift in its AI strategy Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-01-26  Authors: steve kovach, bloomberg, getty images
Keywords: news, cnbc, companies, 200, shift, ai, apple, dismissal, strategy, learning, company, car, apples, google, privacy, employees, points, machine, selfdriving, questions


Apple's dismissal of 200 self-driving car employees points to a shift in its AI strategy

It’s not often you hear about layoffs at Apple.

So it came as a surprise Wednesday when CNBC learned that Apple was removing 200 employees from its self-driving car unit. Apple confirmed the staffing change, but reading between the lines of a spokesperson’s statement, it sounds like the move is the latest in the company’s broader goal to improve its artificial intelligence and machine learning capabilities as it faces increased competition from rivals Google and Amazon.

“As the team focuses their work on several key areas for 2019, some groups are being moved to projects in other parts of the company, where they will support machine learning and other initiatives, across all of Apple,” the company spokesperson said in a statement to CNBC Wednesday.

Self-driving car technology may still be an important initiative at Apple. But reading between the lines, it looks like it’s taking a back seat a Apple beefs up its general AI staff.

“I think they’re making the decision that, at least in the near term, it’s better to have these people doing AI in other projects,” said Gene Munster, a venture capitalist and analyst at Loup Ventures.

Apple’s self-driving car project, called Titan internally, started out with the desire to create an Apple-branded electric car, The Wall Street Journal reported in 2015. But over the last few years, Apple has scaled back its ambition and lost leaders and other employees in the process. Today, the unit mostly explores the underlying technology that makes self-driving cars possible. CEO Tim Cook has repeatedly called self-driving “the mother of all AI projects.”

Since Apple started its self-driving division, the consumer AI space has exploded through the rise of digital assistants like Amazon Alexa and Google Assistant and devices like Amazon’s Echo. Apple’s own digital Assistant, Siri, had a head start when it launched on the iPhone 4S back in 2011, but has not kept up with the competition.

To address the shortfall, Applehired Google’s head of AI John Giannandrea away from the search giant in April. Within a few months, Apple had reorganized its entire AI and machine learning teams under Giannandrea, the company announced to TechCrunch. And just last month, Giannandrea was promoted to Apple’s executive team as vice president of machine learning and artificial intelligence strategy.

Self-driving may still be an important piece to Apple’s AI research. The company said in its statement Wednesday: “We continue to believe there is a huge opportunity with autonomous systems, that Apple has unique capabilities to contribute, and that this is the most ambitious machine learning project ever.”

But as far as products go, competition in self-driving and electric vehicles has grown dramatically in the last four years.

Waymo, Alphabet’s self-driving car company, recently opened up its self-driving car service to the public in Phoenix, Ariz., and is widely considered to be the leaders in self driving. Legacy car companies like GM working on self-driving technology. And it’s not just Tesla making electric cars. Porsche, Audi, Mercedes and other legacy car companies have all announced electric vehicles. It’s hard to imagine how Apple would stand out.

“The sense that I had is they’re not as far along as I had hoped,” Munster said of Apple’s decision to remove the 200 employees out of its car division. “But they still have initiative there.”

Giannandrea’s rapid rise at Apple is the biggest signal yet that Apple intends to invest a lot of time, money and talent in improving AI. Plus, according to leaked comments from Cook at a recent company all-hands meeting reported by Bloomberg, Apple plans to continue hiring in AI “at a strong pace” even as it slows down hiring in other divisions.

In short, we’re seeing Apple eliminate jobs in self-driving and increase the number of people working more broadly on AI.

It may already be paying off. Late last year, a study from Munster’s company, Loup Ventures, showed Siri vastly improved its ability to correctly answer a series of 800 questions. The Loup study said Siri answered 74.6 percent of the questions correctly, up 22 percentage points from just nine months earlier. By comparison, Google Assistant answered 87.9 percent of the questions correctly. Alexa got 72.5 percent of the questions right.

It’s not just about getting questions right, though. The messier problem for Apple is training its AI while convincing users that it’s keeping their data secure.

Google trains its AI systems in part using the massive amounts of public data available on YouTube and the Google search engine. (It’s also started using a program that strives to protect users’ data.)

But Apple has taken a hard stance against unfettered data collection, and promotes its concern over user privacy as a reason to buy its products. In a speech in Brussels last year, Cook called the privacy practices of companies like Google “surveillance,” for example. It also put up a giant ad about its privacy stance in in Las Vegas during CES earlier this month.

So Apple will have to continue to improve its AI while sticking to its goal of keeping people’s personal information private.

“I think it’s very clear Apple is a believer in AI and most of the products will be very subtle about how AI is used,” Munster said.

WATCH: Apple CEO Tim Cook writes op-ed calling for tech privacy regulation


Company: cnbc, Activity: cnbc, Date: 2019-01-26  Authors: steve kovach, bloomberg, getty images
Keywords: news, cnbc, companies, 200, shift, ai, apple, dismissal, strategy, learning, company, car, apples, google, privacy, employees, points, machine, selfdriving, questions


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Apple lays off over 200 from Project Titan autonomous vehicle group

Apple dismissed just over 200 employees this week from Project Titan, its stealthy autonomous vehicle group, people familiar with the matter told CNBC. An Apple spokesperson acknowledged the lay-offs and said the company still sees opportunity in the space:”We have an incredibly talented team working on autonomous systems and associated technologies at Apple. As the team focuses their work on several key areas for 2019, some groups are being moved to projects in other parts of the company, where


Apple dismissed just over 200 employees this week from Project Titan, its stealthy autonomous vehicle group, people familiar with the matter told CNBC. An Apple spokesperson acknowledged the lay-offs and said the company still sees opportunity in the space:”We have an incredibly talented team working on autonomous systems and associated technologies at Apple. As the team focuses their work on several key areas for 2019, some groups are being moved to projects in other parts of the company, where
Apple lays off over 200 from Project Titan autonomous vehicle group Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-01-24  Authors: lora kolodny, christina farr, brendan mcdermid
Keywords: news, cnbc, companies, autonomous, group, lays, systems, 200, machine, apple, company, learning, vehicle, opportunity, team, titan, project, spokesperson


Apple lays off over 200 from Project Titan autonomous vehicle group

Apple dismissed just over 200 employees this week from Project Titan, its stealthy autonomous vehicle group, people familiar with the matter told CNBC.

An Apple spokesperson acknowledged the lay-offs and said the company still sees opportunity in the space:

“We have an incredibly talented team working on autonomous systems and associated technologies at Apple. As the team focuses their work on several key areas for 2019, some groups are being moved to projects in other parts of the company, where they will support machine learning and other initiatives, across all of Apple,” the spokesperson said.

“We continue to believe there is a huge opportunity with autonomous systems, that Apple has unique capabilities to contribute, and that this is the most ambitious machine learning project ever,” they added.


Company: cnbc, Activity: cnbc, Date: 2019-01-24  Authors: lora kolodny, christina farr, brendan mcdermid
Keywords: news, cnbc, companies, autonomous, group, lays, systems, 200, machine, apple, company, learning, vehicle, opportunity, team, titan, project, spokesperson


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Facebook, Samsung engineers quit to form A.I. start-up Fiddler Labs

because there is an ensemble of machine learning models at play,” Gade told CNBC. The apps relied on machine learning models to recommend products to users. In October, the pair quit their companies and co-founded Fiddler Labs, a Mountain View, California, start-up that is building an explainable AI engine. In the past two years, numerous research papers have been published about how to build AI models that can be explained. The idea is Fiddler Labs’ explainable AI engine will allow companies to


because there is an ensemble of machine learning models at play,” Gade told CNBC. The apps relied on machine learning models to recommend products to users. In October, the pair quit their companies and co-founded Fiddler Labs, a Mountain View, California, start-up that is building an explainable AI engine. In the past two years, numerous research papers have been published about how to build AI models that can be explained. The idea is Fiddler Labs’ explainable AI engine will allow companies to
Facebook, Samsung engineers quit to form A.I. start-up Fiddler Labs Cached Page below :
Company: cnbc, Activity: cnbc, Date: 2019-01-23  Authors: salvador rodriguez, fiddler labs
Keywords: news, cnbc, companies, machine, paka, form, engineers, facebook, models, learning, company, startup, quit, build, labs, fiddler, ai, samsung, gade, companies


Facebook, Samsung engineers quit to form A.I. start-up Fiddler Labs

These days, nearly every company is using artificial intelligence and machine learning to help make critical business decisions. But few companies have an idea how the systems they employ actually work.

As an engineering manager working on Facebook’s News Feed for nearly two years, Krishna Gade got a firsthand look at how difficult it can be for companies to understand their own machine learning models.

“It became very difficult for even people within Facebook to be able to reason about ‘Hey, how is News Feed working?’ because there is an ensemble of machine learning models at play,” Gade told CNBC.

“We needed to build tools and platforms to unlock this thing and provide those insights to an engineer all the way to an executive within Facebook.”

Amit Paka, a former colleague and classmate of Gade’s, had a similar experience when he was with Samsung, where he worked on the company’s shopping apps. The apps relied on machine learning models to recommend products to users.

“Some of the challenges there were measuring the return on investment,” Paka said. “How do you compare performance of an old model with a new model?”

After working on these problems, Gade and Paka realized companies might want tools to help understand their artificial intelligence technology. In October, the pair quit their companies and co-founded Fiddler Labs, a Mountain View, California, start-up that is building an explainable AI engine.

“When you build models you don’t know really intrinsically what features are impacting the models. It’s pretty much a black box,” said Gade, Fiddler Labs’ CEO. “What we’re providing is a model that unlocks the black box.”

Fiddler Labs’ arrival comes at a crossroads for the world of AI. In the past two years, numerous research papers have been published about how to build AI models that can be explained. The company is using methods outlined in that research to build its products.

At the same, the demand for explainable AI is on the rise. Last year, the European Union implemented the General Data Protection Regulation. Article 22 of GDPR states that Europeans have the right to obtain an explanation for how automated decisions that have a significant impact on their lives are reached.

“Models increasingly are going to be important in the way we make a bunch of decisions, so asking for some level of accountability just makes a lot of sense,” said James Cham, a partner at Bloomberg Beta, which has invested in the company. “I don’t think GDPR is a one-off thing, but rather part of a larger trend as countries all over the world try to figure this out.”

To kick off, Fiddler Labs has raised $3 million in a seed round led by Lightspeed Venture Partners with participation by Bloomberg Beta and Haystack, and it plans to launch its explainable AI engine in mid-2019, Gade and Paka said.

For now, the company is focused on hiring and expanding its team. It is also amassing a pool of design partners who can test their product and provide feedback. The idea is Fiddler Labs’ explainable AI engine will allow companies to analyze, manage and deploy their machine learning models at scale. The goal is for these tools to provide simplicity so that anyone from a data scientist to a company executive can understand their AI technology.

“The long-term vision is to help enterprises build trustworthy AI experiences for their customers,” Paka said.

WATCH: A.I., data economy the start of a ‘revolution,’ says Blackstone CEO


Company: cnbc, Activity: cnbc, Date: 2019-01-23  Authors: salvador rodriguez, fiddler labs
Keywords: news, cnbc, companies, machine, paka, form, engineers, facebook, models, learning, company, startup, quit, build, labs, fiddler, ai, samsung, gade, companies


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