Sidewalk Labs spins out urban data-gathering tool Replica into a company – gpgmail


Replica, the data-gathering tool created within Sidewalk Labs that maps the movement of people in cities, is now a company.

The newly formed company, which is headed by Nick Bowden, also announced Thursday it has raised $11 million in a Series A funding round from investors Innovation Endeavors, Firebrand Ventures and Revolution’s Rise of the Rest Seed Fund. The capital will be used to accelerate Replica’s growth through new hires beyond its existing 13-person staff, expansion to new cities and investment in its technology.

Replica will remain connected to Sidewalk Labs, the smart city technology firm owned by Google’s parent company Alphabet. Both Sidewalk Labs and Innovation Endeavors will be on the company’s board.

Replica, which is headquartered in Kansas City, with an engineering office in San Francisco, plans to launch in several new regions. Replica is already working with Kansas City, Portland, Chicago and Sacramento, with more cities to come this year.

The Replica tool, which has drawn the ire of some privacy advocates, grew out of Model Lab, a project  started two years ago to investigate modeling as a way to address urban problems. Early work focused on meeting with public agencies throughout the world to learn more about the data, processes and other tools they used.

The Replica planning tool was born out what they discovered: Public agencies don’t have all the information needed to understand the link and interdependence between transportation and land use. The upshot is an incomplete picture of how people move within cities, leaving public agencies ill-equipped to make decisions about how land is used and what transportation is needed and where, the company says.

“Answering questions like who uses the street, in which way and why, are critical for city planners as they work to make transit and land use more efficient and sustainable,” Bowden wrote. “But current resources available to city planners to analyze people’s travel in urban areas are less than satisfactory.”

The Replica modeling tool uses de-identified mobile location data to give public agencies a comprehensive portrait of how, when and why people travel. Movement models are matched to a synthetic population, which has been created using samples of census demographic data to create a broad new data set that is statistically representative of the actual population. The result, Bowden says, is a model that is both privacy-sensitive and extremely useful for public agencies.

Bowden tried to quell privacy worries Thursday in a blog post, emphasizing that the data has been “de-identified,” meaning that an individual’s location data would be identifiable. The company says it’s not interested in the movement of individuals. Instead, the modeling tool is used to see and understand patterns of movement.

“For this reason, we only start with data that has been de-identified,” Bowden wrote Thursday. “This data is then used to train a travel behavior model — basically, a set of rules to represent the movement in a particular place.”


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Google lets David Drummond do the talking – gpgmail


Anyone wondering if Alphabet might reprimand its chief legal officer, David Drummond, for a long-ago extramarital, inter-office affair that continues to be a distraction to the company, the answer seems to be . . . not right now. Though a former subordinate outlined in greater detail than ever yesterday the “hell” she says she has endured in the years since her break-up with Drummond, including a custody battle for their son that she won, Google said today it is not sharing a statement on the matter.

Instead, we were pointed by Google to the personal statement that Drummond issued this afternoon, wherein he acknowledges the affair with Jennifer Blakely, a former senior contracts manager with the company during a time when Drummond was Google’s general counsel.

As BuzzFeed notes, he doesn’t apologize to Blakely, saying instead of their “difficult break-up 10 years ago” that “I am far from perfect and I regret my part in that.” He also emphasizes that there are “two sides to all of the conversations and details Jennifer recounts,” saying that he takes a “very different view about what happened.”

Drummond’s full statement:

It’s not a secret that Jennifer and I had a difficult break-up 10 years ago. I am far from perfect and I regret my part in that.

Her account raises many claims about us and other people, including our son and my former wife. As you would expect, there are two sides to all of the conversations and details Jennifer recounts, and I take a very different view about what happened. I have discussed these claims directly with Jennifer, and I addressed the details of our relationship with our employer at the time.

But I do want to address one claim that touches on professional matters. Other than Jennifer, I never started a relationship with anyone else who was working at Google or Alphabet. Any suggestion otherwise is simply untrue.

I know Jennifer feels wronged and understand that she wants to speak out about it. But I won’t be getting into a public back and forth about these personal matters.”

Drummond is presumably hoping that by acknowledging Blakely’s post, the affair will recede again into the background, and it might. Drummond has enjoyed the support of the company for the last 17 years, even while Google officially recognized the affair back in 2007.

On the other hand, other powerful people who’ve come under scrutiny for their decision-making have discovered they have discovered they have less control over a situation than they imagined. While Alphabet isn’t a democracy, Google employees have shown they’re willing to flex their muscle if need be to force change on the company, and Blakely’s account has seemingly infuriated anew many who say the company’s culture has always been, and continues to be discriminatory toward women.


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Waymo self-driving cars head to Florida for rainy season – gpgmail


Waymo is taking some of its autonomous vehicles to Florida just in time for hurricane season to begin testing in heavy rain.

The move to Florida will focus on testing how its myriad of sensors hold up during the region’s rainy season as well as to collect data. All of the vehicles will be manually driven by trained drivers.

Waymo will bring both of its autonomous vehicles, the Chrysler Pacificas and a Jaguar I-Pace, to Naples and Miami, Florida for testing, according to a blog posted Tuesday. Miami is one of the wettest cities in the U.S., averaging 61.9 inches of rain annually.

The self-driving car company, which is a business under Alphabet, began testing its autonomous vehicles in and around Mountain View, Calif., before branching out to other cities and weather, including Novi, Michigan, Kirkland, Washington and San Francisco. But the bulk of the company’s activities have been in suburbs of Phoenix and around Mountain View — two places with lots of sun, and even blowing dust, in the case of Phoenix.

Waymo opened a technical center Chandler, Ariz. and started testing there in 2016. Since then the company has ramped up its testing and launched an early rider program in April 2017 as a step toward commercial deployment.

The company will spend the next several weeks driving on a closed course in Naples to test its sensor suite , which includes lidar, cameras and radar . Later in the month, Waymo plans to bring its vehicles to public roads in Miami. A few Waymo vehicles will be collecting data on highways between Orlando, Tampa, Fort Myers and Miami.

Waymo is hardly the only autonomous vehicle company to take advantage of Florida’s AV friendly regulations. Ford and Argo AI, the self-driving company it backs, have had a presence in the Miami since early 2018. Argo AI began collecting data and mapping and has since expanded to testing in autonomous mode last summer.

Last year, Ford partnered with Walmart and Postmates to test the business of delivering goods like groceries and pet food using self-driving vehicles. The pilot project is focused on Miami-Dade County.

Self-driving trucks startup Starsky Robotics also is testing in Florida.


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Racial bias observed in hate speech detection algorithm from Google – gpgmail


Understanding what makes something offensive or hurtful is difficult enough that many people can’t figure it out, let alone AI systems. And people of color are frequently left out of AI training sets. So it’s little surprise that Alphabet/Google -spawned Jigsaw manages to trip over both of these issues at once, flagging slang used by black Americans as toxic.

To be clear, the study was not specifically about evaluating the company’s hate speech detection algorithm, which has faced issues before. Instead it is cited as a contemporary attempt to computationally dissect speech and assign a “toxicity score” — and that it appears to fail in a way indicative of bias against black American speech patterns.

The researchers, at the University of Washington, were interested in the idea that databases of hate speech currently available might have racial biases baked in — like many other datasets that suffered from a lack of inclusive practices during formation.

They looked at a handful of such databases, essentially thousands of tweets annotated by people as being “hateful,” “offensive,” “abusive,” and so on. These databases were also analyzed to find language strongly associated with African American English or white-aligned English.

Combining these two sets basically let them see whether white or black vernacular had a higher or lower chance of being labeled offensive. Lo and behold, black-aligned English was much more likely to be labeled offensive.

For both datasets, we uncover strong associations between inferred AAE dialect and various hate speech categories, specifically the “offensive” label from DWMW 17 (r = 0.42) and the “abusive” label from FDCL 18 (r = 0.35), providing evidence that dialect-based bias is present in these corpora.

The experiment continued with the researchers sourcing their own annotations for tweets, and found that similar biases appeared. But by “priming” annotators with the knowledge that the person tweeting was likely black or using black-aligned English, the likelihood that they would label a tweet offensive dropped considerably.

Examples of control, dialect priming, and race priming for annotators.

This isn’t to say necessarily that annotators are all racist or anything like that. But the job of determining what is and isn’t offensive is a complex one socially and linguistically, and obviously awareness of the speaker’s identity is important in some cases, especially in cases where terms once used derisively to refer to that identity have been reclaimed.

What’s all this got to do with Alphabet, or Jigsaw, or Google? Well, Jigsaw is a company built out of Alphabet — which we all really just think of as Google by another name — with the intention of helping moderate online discussion by automatically detecting (among other things) offensive speech. Its PerspectiveAPI lets people input a snippet of text and receive a “toxicity score.”

As part of the experiment, the researchers fed a bunch of the tweets in question to Perspective. What they got saw was “correlations between dialects/groups in our datasets and the Perspective toxicity scores. All correlations are significant, which indicates potential racial bias for all datasets.”

chart perspe

Chart showing that African American English (AAE) was more likely to be labeled toxic by Alphabet’s Perspective API.

So basically, they found that Perspective was way more likely to label black speech as toxic, and white speech otherwise. Remember, this isn’t a model thrown together on the back of a few thousand tweets — it’s an attempt at a commercial moderation product.

As this comparison wasn’t the primary goal of the research, but rather a byproduct, it should not be taken as some kind of massive takedown of Jigsaw’s work. On the other hand, the differences shown are very significant and quite in keeping with the rest of the team’s findings. At the very least it is, as with the other datasets evaluated, a signal that the processes involved in their creation need to be reevaluated.

I’ve asked the researchers for a bit more information on the paper and will update this post if I hear back. In the meantime you can read the full paper, which was presented at the Proceedings of the Association for Computational Linguistics in Florence, below:

The Risk of Racial Bias in Hate Speech Detection by gpgmail on Scribd


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Another day, another reversal in stock fortunes as recession fears grow – gpgmail


U.S. stock markets plummeted today as recession fears continue to grow.

Yesterday’s good news about a reprieve on tariffs for U.S. consumer imports was undone by increasing concerns over economic indicators pointing to a potential global recession coming within the next year.

The Dow Jones Industrial Average dropped more than 800 points on Wednesday — its largest decline of the year — while the S&P 500 fell by 85 points and the tech-heavy Nasdaq dropped 240 points.

The downturn in the markets came a day after the Dow closed up 373 points after the U.S. Trade Representative announced a delay in many of the import taxes imposed by the Trump administration planned to impose on Chinese goods.

In the U.S. it was concerns over the news that the yield on 10-year U.S. Treasury notes had dipped below the yield of two-year notes. It’s an indicator that investors think the short term prospects for a country’s economic outlook are worse than the long term outlook and so yields are higher for short term investments.

China’s industrial and retail sectors both slowed significantly in July. Industrial production including manufacturing, mining and utilities grew by 4.8 percent in July (a steep decline from 6.3% growth in June).  Meanwhile retail sales in the country slowed to 7.6 percent, down from 9.8 percent in June.

Germany also posted declines over the summer months indicating that its economy had contracted by 0.1% in the three months to June.

Globally, the protracted trade war between the U.S. and China are weighing on economies — as are concerns about what a hard Brexit would mean for the economies in the European Union .

The stocks of Alphabet, Amazon, Apple, Facebook, Microsoft, Netflix, and Salesforce, were all off by somewhere between 2.5% and 4.5% in today’s trading.


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Tech stocks walloped as China retaliates in the latest salvo of its trade war with the U.S. – gpgmail


All U.S. stock markets were down severely today, and tech stocks were hit especially hard, as China retaliated to increasing U.S. tariffs by halting imports on U.S. agricultural goods and finally acceded to market pressures by letting the yuan slide in value against the dollar.

At one point, the Dow was down nearly 900 points before staging a late afternoon rally to close off by roughly 760 points. The Nasdaq, the marketplace which is home to a number of technology stocks, saw its value drop by 3.4% or 277.10 points.

Shares of Alphabet (the parent company of Google), Amazon, Apple, Facebook, Microsoft, Netflix, and Twitter were all down for the day. Indeed, as CNBC reported, the biggest tech stocks, Microsoft, Amazon, Apple, Facebook, and Alphabet lost a combined $162 billion in market value.

Declines came as China allowed its currency to fall below what was once considered to be a red-line in the country’s currency peg against the dollar. That means that Chinese goods start to look more attractive globally as their prices decline in relation to the dollar. It could also trigger a wave of currency devaluations and protectionist measures across the globe — further putting downward pressure on global economic growth.

Stocks also continued to feel the pinch from the threat that President Donald Trump would make good on his threat to impose new tariffs on goods from China beginning September 1, 2019. Those tariffs are expected to take a bite into every day consumer goods and clothing, which adversely affects tech companies.

The big concern for these tech companies is the looming threat of that tariff expansion from the U.S. If those tariffs go into effect it would have significant consequences in these companies’ home market. 

“Assuming smartphones, tablets, smart watches, and computer systems are not categorically excluded from the final $300B tranche, we expect there will be material impact to Apple hardware product earnings,” analysts from Cowen & Co. wrote in a note quoted by CNBC .


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Google says it doubled Pixel sales year-over-year – gpgmail


It looks like the mid-range Pixel 3a is the hit Google surely hoped it would be.

Alphabet reported some pretty good earnings today, but the company’s report tends to be pretty generic, given that it doesn’t provide details for its different business units inside of Google and its other segments. That’s not to say there isn’t good news there for Google. On today’s call, Google CEO Sundar Pichai shared some new stats for the company’s phone line.

“With the launch of Pixel 3a in May, overall Pixel unit sales in Q2 grew more than 2x year-over-year,” Pichai announced. Part of this growth, he noted, is due to Google greatly expanded its distribution network beyond its own store and Verizon to also include T Mobile, Sprint, US Cellular, Spectrum Mobile and others. He also stressed that the Pixel 3a received Google’s highest Net Promotor Score rating yet.

We don’t, of course, know, what the baseline for Pichai’s claim here is, since Google never shared any actual sales numbers, but it surely helps that the Pixel 3a is relatively affordable and compares well to flagship phones without any major trade-offs. When it launched, reviews were generally very positive, too, which surely helped as well. Unlike previous Pixel launches, the first batch of Pixel 3a phones also didn’t face any major hardware problems, something that regularly plagued Google’s earlier efforts.



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Microsoft and the second SoftBank Vision Fund as another play for corporate cloud dominance – gpgmail


It looks like the return of SoftBank’s Vision Fund may be less reliant on murder money and more reliant on Microsoft’s money-making machine for its backing.

The rumored involvement of Microsoft in financing SoftBank Vision Fund II (electric boogaloo?) is interesting for what it may indicate about how the relationship between venture investors, startups and the large corporations that dominate the tech industry are changing.

If the name of the game is platform and services, then corporate behemoths like Microsoft, Alphabet, Amazon and Apple are in interesting positions to invest in startups as a flywheel for growth in some of their most profitable and strategic business units.

To some extent this has always been true, but it’s becoming more important now as web services become larger slices of the corporate balance sheet at these three companies (particularly — although IBM is also playing in this game). Basically, like corporate accelerators and venture arms, investing in SoftBank is another service that’s being potentially offered to lock in startups to corporate cloud ecosystems.

While there are no guarantees that a nudge from an investor to use one tech platform for web services over another would make any difference, it’s clear that big tech companies like Amazon, Alphabet and Microsoft are all over startups to use one web stack over another.

Amazon has tied itself ever more tightly to the Techstars ecosystem of incubators for new tech companies, Microsoft has its own corporate accelerator programs and investment arm and Alphabet does the same.

As technology continues to advance, the big companies have more services they can offer to tech companies that will be increasingly more compelling and drive increasing revenue.

All three big companies mentioned above (and even IBM, bless its big blue non-existent heart) have machine learning tools that they’d love to provide as a service to startups as well. And even as IBM sunsets Watson as a balance sheet item (an event that was an elementary conclusion to anyone who has tracked its long, slow spiral), machine learning services are going to become a larger slice of revenue for the providers who can effectively tie startups into those services.

Most entrepreneurs pay lip service to the fact that enhanced algorithms are going to become table stakes in new product offerings so observers can watch that become another engine of growth for the big companies that can get it right.

Also, startups are going to increasingly become a sales channel for big tech, even as big tech has traditionally been a sales channel for startups.

Software as a service businesses using a freemium business model have an easier time getting into a corporate environment than Microsoft or Google . And even as the productivity suites from these companies battle it out (Verizon, FWIW, is team Google for now), some of the money flowing to a SaaS company’s coffers from a big corporate entity will ultimately wind up in either Microsoft, Amazon or Alphabet’s returns.

This model also helps venture investors, who now have more assurance that there will be late-stage capital to bolster their businesses (including really, really bad ones), although most traditional firms have a love-hate relationship with Masayoshi Son’s gargantuan investment vehicle.

Finally, there’s the simple fact that divorcing SoftBank from Saudi Arabia’s journalist-killing murder money is a good thing for the firm and the larger technology industry, which has enough moral conundrums to consider without adding to the mix another problematic geopolitical relationship.


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