Apple TV+ show ‘Little America’ to get a companion podcast, exec producer says

A recent report from Bloomberg claimed Apple was considering making original podcasts related to its Apple TV+ streaming service shows. Now we have further confirmation that these companion podcasts are indeed in the works. In an interview with Forbes, an executive producer of the Apple TV+ anthology series “Little America,” Lee Eisenberg, talks about the benefits of working with Apple — noting, by the way, that the show will have a podcast as well as a playlist featuring music from the series.

Neither of these has yet to launch, but are in line with what Bloomberg claimed Apple has been planning.

The audio programs — basically Apple’s own original podcasts — would help to market some of Apple TV+’s more high-profile shows. “Little America” was mentioned in Bloomberg’s report as one possibility, given the rave reviews it received from critics. Golden Globe nominee “The Morning Show,” which also won Jennifer Aniston a best actress award at the Screen Actor Guild Awards, was another.

Eisenberg, speaking to Forbes, confirmed the plans to cross-promote the new show across Apple’s platform.

“Apple is such a worldwide and multi-faceted brand,” he said. “We’re doing a podcast to delve more into the stories and the music on the show. There’ll also be a playlist for every episode. We’re putting out a book too. Apple has an infrastructure that just felt like it would be able to touch all of the different pieces that we wanted,” he added.

The comment was meant to highlight one of the benefits of working with a company like Apple, in a piece that laid out how different Apple’s approach is from rival networks and streaming services. For example, Apple was passionate about “Little America,” which focuses on the immigrant experience in America, even when traditional networks had passed with concerns over subject matter and lack of star power. In fact, Apple sold itself and its streaming service to “Little America’s” producers and creators, not the other way around.

It’s unclear when the “Little America” podcast or episode playlists will go live or to what extent Apple will be involved when they do. Apple has not responded to requests for comment on the matter.

Such a move would represent a big jump by Apple into the world of original podcasts, if and when it comes to pass. Today, the company’s selection of Apple-produced podcasts are limited to things like Apple keynotes, special events, and quarterly earnings calls — not really what you think of as original audio programming.

Apple is alone among the top streaming services in terms of not having some sort of original audio programming play. Spotify has heavily invested in podcasts, and now has hundreds of originals and exclusives available to its users. It also acquired several podcast networks and podcast startups, including GimletParcast, and Anchor. It’s now said to be in discussions with The Ringer. 

Pandora is leveraging the assets of new parent SiriusXM to turn its talk shows into podcasts and develop a new podcast-and-audio format, called Pandora Stories.

Meanwhile, Amazon Music — now close to Apple in user numberswraps in a premium collection of Audible podcasts with its Prime membership. That means Amazon Prime subscribers get both free music as well as exclusives audio shows from Audible.

Even a smaller player, Stitcher, offers its own network of originals.

It seems original audio programming is something that’s now becoming table-stakes in the streaming music wars. Apple’s entry may be belated, but it will at least be differentiated as its podcasts will promote its shows and vice versa, instead of only being connected to music.

 

via Click on the link for the full article

Layoffs hit Q&A startup Quora

Quora, a ten-year-old question-and-answer startup based in Mountain View, is laying off staff in its Bay Area and New York offices, the company’s CEO announced on the site today.

Like other startup leaders being pushed by investors to focus more heavily on cashflow, CEO Adam D’Angelo wrote that the layoffs and “organizational changes” were being pursued in order to focus on “scaling the organization in a financially responsible way.”

D’Angelo did not disclose the scale of the layoffs. Recode reported last year that Quora was locking down $60 million at a $2 billion valuation, noting at the time that the startup had around 200 employees. The company has publicly disclosed $225 million to date according to Crunchbase from investors including Benchmark, Peter Thiel and Y Combinator.

We’ve reached out to the company for additional comment.

“[W]e need to reduce our burn rate to a sustainable level from which we can focus on pursuing the mission and growing the business over the long term. We do not want to be dependent on outside capital, so self-reliance and careful management of our resources are crucial to our future,” D’Angelo wrote.

Over the past several weeks, layoffs have been hitting startups including several in SoftBank’s portfolio as well as Mozilla, and just today, genetic testing startup 23andMe.

via Click on the link for the full article

Uber’s self-driving unit starts mapping Washington, D.C. ahead of testing

Uber Advanced Technologies Group will start mapping Washington, D.C., ahead of plans to begin testing its self-driving vehicles in the city this year.

Initially, there will be three Uber vehicles mapping the area, a company spokesperson said. These vehicles, which will be manually driven and have two trained employees inside, will collect sensor data using a top-mounted sensor wing equipped with cameras and a spinning lidar. The data will be used to build high-definition maps. The data will also be used for Uber’s virtual simulation and test track testing scenarios.

Uber intends to launch autonomous vehicles in Washington, D.C. before the end of 2020.

At least one other company is already testing self-driving cars in Washington, D.C. Ford announced in October 2018 plans to test its autonomous vehicles in Washington, D.C. Argo AI is developing the virtual driver system and high-definition maps designed for Ford’s self-driving vehicles.

Argo, which is backed by Ford and Volkswagen, started mapping the city in 2018. Testing was expected to begin in the first quarter of 2019.

Uber ATG has kept a low profile ever since one of its human-supervised test vehicles struck and killed a pedestrian in Tempe, Ariz. in March 2018. The company halted its entire autonomous vehicle operation immediately following the incident.

Nine months later, Uber ATG resumed on-road testing of its self-driving vehicles in Pittsburgh, following a Pennsylvania Department of Transportation decision to authorize the company to put its autonomous vehicles on public roads. The company hasn’t resumed testing in other markets, such as San Francisco.

Uber is collecting data and mapping in three other cities: Dallas, San Francisco and Toronto. In those cities, just like in Washington, D.C., Uber manually drives its test vehicles.

Uber spun out the self-driving car business in April 2019 after closing $1 billion in funding from Toyota, auto-parts maker Denso and SoftBank’s Vision Fund. The deal valued Uber ATG at $7.25 billion at the time of the announcement. Under the deal, Toyota and Denso are providing $667 million, with the Vision Fund throwing in the remaining $333 million.

via Click on the link for the full article

Google’s Dataset Search comes out of beta

Google today announced that Dataset Search, a service that lets you search for close to 25 million different publicly available datasets, is now out of beta. Dataset Search first launched in September 2018.

Researchers can use these datasets, which range from pretty small ones that tell you how many cats there were in the Netherlands from 2010 to 2018 to large annotated audio and image sets, to check their hypotheses or train and test their machine learning models. The tool currently indexes about 6 million tables.

With this release, Dataset Search is getting a mobile version and Google is also adding a few new features to Dataset Search. The first of these is a new filter that lets you choose which type of dataset you want to see (tables, images, text, etc.), which makes it easier to find the right data you’re looking for. In addition, the company has added more information about the datasets and the organizations that publish them.

A lot of the data in the search index comes from government agencies. In total, Google says, there are about 2 million U.S. government datasets in the index right now. But you’ll also regularly find Google’s own Kaggle show up, as well as a number of other public and private organizations that make public data available as well.

As Google notes, anybody who owns an interesting dataset can make it available to be indexed by using a standard schema.org markup to describe the data in more detail.

via Click on the link for the full article

Xerox wants to replace HP board that rejected takeover bid

In Xerox’s latest effort to get HP to bend to its will and combine the two companies, it announced its intent today to try and replace the entire HP Board of Directors at the company’s stockholder’s meeting in April. That would be the same board that unanimously rejected Xerox’s takeover bid.

Xerox and HP have been playing a highly public game of tit for tat in recent months. Xerox wants very much to take to combine with HP, and offered $34 billion, an offer HP summarily rejected at the end of last year. Xerox threatened to take it shareholders.

Now it wants to take over the board, announcing today that it had nominated 11 people to replace the current slate of directors.

As you might imagine, HP was none too pleased with this latest move by Xerox. “We believe these nominations are a self-serving tactic by Xerox to advance its proposal, that significantly undervalues HP and creates meaningful risk to the detriment of HP shareholders,” HP fired back in a statement today emailed to TechCrunch.

It went onto blame Xerox shareholder Carl Icahn for the continued pressure. “We believe that Xerox’s proposal and nominations are being driven by Carl Icahn, and his large ownership position in Xerox means that his interests are not aligned with those of other HP shareholders. Due to Mr. Icahn’s ownership position, he would disproportionately benefit from an acquisition of HP by Xerox at a price that undervalues HP,” the company stated.

The two companies exchanged increasingly harsh letters in November as Xerox signaled its intent to take over the much larger HP. HP questioned Xerox’s ability to raise the money, but earlier this month it announced had in fact raised the $24 billion it would need to buy the company. HP was still not convinced.

Today’s exchange is just the latest between the two companies in an increasingly hostile bid by Xerox to combine the two companies.

via Click on the link for the full article

Waymo’s self-driving trucks and minivans are headed to New Mexico and Texas

Waymo said Thursday it will begin mapping and eventually testing its autonomous long-haul trucks in Texas and parts of New Mexico, the latest sign that the Alphabet company is expanding beyond its core focus of launching a robotaxi business.

Waymo said in a tweet posted early Thursday it had picked these areas because they are “interesting and promising commercial routes.” Waymo also said it would “explore how the Waymo Driver” — the company’s branded self-driving system — could be used to “create new transportation solutions.”

Waymo plans to mostly focus on interstates because Texas has a particularly high freight volume, the company said. The program will begin with mapping conducted by Waymo’s Chrysler Pacifica minivans.

The mapping and eventual testing will occur on highways around Dallas, Houston and El Paso. In New Mexico, Waymo will focus on the southern most part of the state.

Interstate 10 will be a critical stretch of highway in both states — and one that is already a testbed for TuSimple, a self-driving trucking startup that has operations in Tucson and San Diego. TuSimple tests and carries freight along the Tucson to Phoenix corridor on I-10. The company also tests on I-10 in New Mexico and Texas.

 

Waymo, which is best known for its pursuit of a robotaxi service, integrated its self-driving system into Class 8 trucks and began testing them in Arizona in August 2017. The company stopped testing its trucks on Arizona roads sometime later that year. The company brought back its truck testing to Arizona in May 2019.

Those early Arizona tests were aimed at gathering initial information about driving trucks in the region, while the new round of truck testing in Arizona marks a more advanced stage in the program’s development, Waymo said at the time.

Waymo has been testing its self-driving trucks in a handful of locations in the U.S., including Arizona, the San Francisco area and Atlanta. In 2018, the company announced plans to use its self-driving trucks to deliver freight bound for Google’s  data centers in Atlanta.

Waymo’s trucking program has had a higher profile in the past year. In June, Waymo brought on 13 robotics experts, a group that includes Anki’s  co-founder and former CEO Boris Sofman, to lead engineering in the autonomous trucking division.

via Click on the link for the full article

Switching to NoSQL is easier than you might think

While many companies still utilize relational databases, the benefits of NoSQL databases are clear, whether that’s the ability to handle large volumes of structured or unstructured data, perform Agile sprints or its flexibility and scalability. And moving to a NoSQL database is easier than most think.

Brian Hess, the strategic solution engineer at DataStax, explained that SQL is not really the problem to begin with. It’s very straightforward to interact with and it is very common for data to be nature. In fact, most NoSQL databases actually have a SQL-like query language. 

 Instead, the problem is that relational databases struggle with scalability.

“When relational databases came out and really put some structure and formalism around these systems, they really made some promises about what they’re offering to applications and data owners that struggle when you get to scale,” Hess said. “And this is fine, when the data was measured in in kilobytes, megabytes, even gigabytes. But as we get into bigger datasets, we really have problems.”

To ameliorate the problem of scalability, Apache Cassandra, was created in 2008 as a free and open-source, distributed, wide column store (a NoSQL database that uses tables, rows, and columns) database management system. It graduated the Apache Incubator two years later. Cassandra also formed the basis of DataStax’s database for hybrid and multi-cloud.

Now, the Cassandra community is focusing its efforts to revisit consistency and isolation. 

“With a lot of the systems that we see out there, the applications that we’re working with, 100% consistency is not something most applications really need,” Hess said. “And so that’s an area where we’re going to really relax.”

Another area for improvement is isolation, which prevents different queries from interacting with each other and getting in the way. There is currently a very strict way of going about this; however, a less rigid approach would allow for more concurrent users and queries going on in the system at the same time, according to Hess.

Cassandra is designed for high concurrency, lots of queries coming in at the same time, low latency, so very short millisecond or even sometimes faster responses, according to Hess. 

“A lot of times, people will talk about how we’re going to do this very differently. We have to get you to think entirely differently when talking about Cassandra versus a SQL database. And I think that’s not quite right,” Hess said. “It’s not that you’re actually doing different things. You’re doing very similar things,  but you’re doing them by approaching them slightly differently.”

Cassandra still has rows and tables and is referred to as a partitioned-table data model, even though it is still referred to as a wide-column store database by many.The tables then live inside a key space, which is basically a holdover from the former model that used a schema in the relational database. 

“It’s really just the language that’s different and not so much the concept,” Hess explained, adding that the Cassandra Query Language (CQL) also looks an awful lot like the relational SQL. “We really solidified around CQL and this tabular model. The rows and columns are really, really natural. And by having a schema, we can ensure that as the data’s being put in, it’s actually valid.”

Many NoSQL models share similar concepts with RDBMS, whether it’s the SQL-like languages, keyspaces that are analogous to a database in the RDBMS world, or the use of tables, which are similar to RDBMS tables but more flexible and dynamic. 

The post Switching to NoSQL is easier than you might think appeared first on SD Times.

via Click on the link for the full article

Layoffs reach 23andMe after hitting Mozilla and the Vision Fund portfolio

Layoffs in the technology and venture-backed worlds continued today, as 23andMe confirmed to CNBC that it laid off around 100 people, or about 14% of its formerly 700-person staff. The cuts would be notable by themselves, but given how many other reductions have recently been announced, they indicate that a rolling round of belt-tightening amongst well-funded private companies continues.

Mozilla, for example, cut 70 staffers earlier this year. As TechCrunch’s Frederic Lardinois reported earlier in January, the company’s revenue-generating products were taking longer to reach market than expected. And with less revenue coming in than expected, its human footprint had to be reduced.

23andMe and Mozilla are not alone, however. Playful Studios cut staff just this week, 2019 itself saw more than 300% more tech layoffs than in the preceding year and TechCrunch has covered a litany of layoffs at Vision Fund-backed companies over the past few months, including:

Scooter unicorns Lime and Bird have also reduced staff this year. The for-profit drive is firing on all cylinders in the wake of the failed WeWork IPO attempt. WeWork was an outlier in terms of how bad its financial results were, but the fear it introduced to the market appears pretty damn mainstream by this point. (Forsake hope, alle ye whoe require a Series H.)

The money at risk, let alone the human cost, is high. Zume has raised more than $400 million. 23andMe has raised an even sharper $786.1 million. Rappi? How about $1.4 billion. And Oyo? $3.2 billion so farEvery company that loses money eventually dies. And every company that always makes money lives forever. It seems that lots of companies want to jump over the fence, make some money and rebuild investor confidence in their shares.

It’s just too bad that the rank-and-file are taking the brunt of the correction.

via Click on the link for the full article

Cortex Labs helps data scientists deploy machine learning models in the cloud

It’s one thing to develop a working machine learning model, it’s another to put it to work in an application. Cortex Labs is an early stage startup with some open source tooling designed to help data scientists take that last step.

The company’s founders were students at Berkeley when they observed that one of the problems around creating machine learning models was finding a way to deploy them. While there was a lot of open source tooling available, data scientists are not experts in infrastructure.

CEO Omer Spillinger says that infrastructure was something the four members of the founding team — himself, CTO David Eliahu, head of engineering Vishal Bollu and head of growth Caleb Kaiser — understood well.

What the four founders did was take a set of open source tools and combine them with AWS services to provide a way to deploy models more easily. “We take open source tools like TensorFlow, Kubernetes and Docker and we combine them with AWS services like CloudWatch, EKS (Amazon’s flavor of Kubernetes) and S3 to basically give one API for developers to deploy their models,” Spillinger explained.

He says that a data scientist starts by uploading an exported model file to S3 cloud storage. “Then we pull it, containerize it and deploy it on Kubernetes behind the scenes. We automatically scale the workload and automatically switch you to GPUs if it’s compute intensive. We stream logs and expose [the model] to the web. We help you manage security around that, stuff like that,” he said

While he acknowledges this not unlike Amazon SageMaker, the company’s long-term goal is to support all of the major cloud platforms. SageMaker of course only works on the Amazon cloud, while Cortex will eventually work on any cloud. In fact, Spillinger says that the biggest feature request they’ve gotten to this point, is to support Google Cloud. He says that and support for Microsoft Azure are on the road map.

The Cortex founders have been keeping their head above water while they wait for a commercial product with the help of an $888,888 seed round from Engineering Capital in 2018. If you’re wondering about that oddly specific number, it’s partly an inside joke — Spillinger’s birthday is August 8th — and partly a number arrived at to make the valuation work, he said.

For now, the company is offering the open source tools, and building a community of developers and data scientists. Eventually, it wants to monetize by building a cloud service for companies who don’t want to manage clusters — but that is down the road, Spillinger said.

via Click on the link for the full article

As autonomy stalls, lidar companies learn to adapt

Lidar sensors are likely to be essential to autonomous vehicles, but if there are none of the latter, how can you make money with the former? Among the industry executives I spoke with, the outlook is optimistic as they unhitch their wagons from the sputtering star of self-driving cars. As it turns out, a few years of manic investment does wonders for those who have the wisdom to apply it properly.

The show floor at CES 2020 was packed with lidar companies exhibiting in larger spaces, seemingly in greater numbers than before. That seemed at odds with reports that 2019 had been a sort of correction year for the industry, so I met with executives and knowledgeable types at several companies to hear their take on the sector’s transformation over the last couple of years.

As context, 2017 was perhaps peak lidar, nearing the end of several years of nearly feverish investment in a variety of companies. It was less a gold rush than a speculative land rush: autonomous vehicles were purportedly right around the corner and each would need a lidar unit… or five. The race to invest in a winner was on, leading to an explosion of companies claiming ascendancy over their rivals.

Unfortunately, as many will recall, autonomous cars seem to be no closer today than they were then, as the true difficulty of the task dawned on those undertaking it.

via Click on the link for the full article