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Judge Tells Uber It ‘Misled The Court’, Slams Waymo For ‘Being Greedy’

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Both Uber and Waymo found themselves being scolded by a federal judge who called one side “greedy” and accused the other of repeatedly misleading the court.

During a tension-filled court hearing on Wednesday in San Francisco, Waymo asked the court to hold Uber and its lawyers in contempt for dragging their feet when it comes to disclosing information about documents in their possession.

U.S. District Judge William Alsup, who is presiding over the high-profile suit between the two companies, specifically called out Uber’s lawyer, Arturo Gonzalez of Morrison & Foerster, for misleading the court “time and time again.”

At one point, Alsup even threatened to have Gonzalez take the stand during the upcoming trial to explain why Uber has been slow to respond to request for documents, including the 14,000 files that were allegedly stolen from Google by an engineer who went on to lead Uber’s self-driving car efforts.

“You’ll be a good witness. You’ll be right there explaining to the jury and explaining this story,” Alsup told Uber’s lawyer, pointing to the stand next to him.

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While there’s a chance Gonzalez could still take the stand during trial, Alsup seemed more inclined to let the jury hear about the many deadlines Uber’s legal team missed or dodged in the lead-up to the trial, which is scheduled to begin in October.

“I am concerned that Mr. Gonzalez failed to disclose that he had the documents and took a long time to come clean,” Alsup said. “I am inclined… to tell the jury exactly this scenario: that he was ordered to come clean, did not come clean, ordered to come clean again, and did not come clean — finally in June or July came clean.”

In a heated exchange, Gonzalez fired back at the judge for buying into a “completely false premise” and said there will never be a time when anyone proves that his firm or Uber ever concealed the 14,000 documents.

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While much of Alsup’s scolding was directed at Uber, he wasn’t happy with Waymo either.

In a previous court order, the Google spin-off company had to narrow down its list of trade secret violations from over 100 to nine to be argued at trial. When Waymo asked to retain the right to argue the rest, Alsup said if it wanted the whole lot, he could postpone the case for a year, potentially to Waymo’s own detriment.

“You can’t have everything,” Alsup said. “You want 121? I’ll give you that. We can push this out another couple of years and they’ll have cars on the street because you’re being greedy.”

In the end, Waymo acquiesced and agreed to move forward with their limited selection. The case, in which Uber’s lawyers said could involve “potentially multi-billion dollar damages,” is scheduled to begin in early October. – Written by 

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The Nearly $2 Million Aston Martin Valhalla Is A Gift From The Gods

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Proving, again, there is often truth to rumor, Aston Martin chief executive Andy Palmer confirmed that the previously code-named Aston Martin AM-RB-003 s hypercar will be officially called Valhalla, continuing with the manufacturer’s Norse god naming theme.

“Norse mythology contains such powerful language and rich storytelling it felt only right that the AM-RB 003 should follow the Valkyrie’s theme,” Palmer told reporters.

“For those fortunate enough to own one I’m sure they will recognize and appreciate the name’s connotations of glory and happiness, for there can be few more hallowed places than the driver’s seat of an Aston Martin Valhalla.”

Inside the new Aston Martin Valhalla.
Speed Racer: The dash might be minimal, but the F1-style steering wheel is anything but. ASTON MARTIN

Joining the stunning Valkyrie and extreme Valkyrie AMR Pro, the all-new gift from the gods will compete for bragging rights with the likes of the Ferrari LaFerrari and the McLaren Senna.

As we reported earlier this year, only 500 of the hybrid hypercar will be built, every single one of them clad entirely in carbon fiber.

Aston Martin Valkyrie.
Sibling Rivalry: The Valhalla borrows much of its styling from older brother, the Valkyrie (shown here). ASTON MARTIN

The Valhalla will look much like its bigger brother, the Valkyrie (the rear diffuser and air tunnels appear to be nearly identical). However, it will sport a more traditional mid-engine supercar layout, with high-exit exhausts, a jet-fighter-style canopy, and active aerodynamics and suspension.

It will be powered by an all-new V6 engine that will feature some level of hybridization and turbocharging to aid performance. Total output: 1,000 horsepower. However, that is still just a rumor. We’ll have to wait and see. Also available will be an 8-speed F1-inspired dual-clutch transmission, a limited-slip differential and an e-AWD system.

All new Aston Martin Valhalla
Powerful Beast: The Valhalla’s turbocharged hybrid V-6 is expected to develop 1,000 horsepower.ASTON MARTIN

Aston Martin is targeting a 0-62 mph sprint time of 2.5 seconds and a top speed of more than 220 mph.

If you don’t have the almost $2 million ticket to ride this 200 mph-plus hybrid hypercar, you can see it in the upcoming 007 movie now in production starring Daniel Craig as James Bond. It is set to be one of a trio of Aston Martins to appear in the film. Send me a secure tip.

-Chuck Tannert; Forbes Staff

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How Google Is Using AI To Make Voice Recognition Work For People With Disabilities

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Want to schedule an appointment? Just ask your phone. Need to turn on your bedroom lights? Google Home has you covered.

Now a $49 billion market, voice-activated systems have gained popularity among consumers, thanks to their ability to automate and streamline mundane tasks. But for people with impaired speech,  technologies that rely on voice commands have proved to be far from perfect.

That’s the impetus for Google’s newly formed Project Euphonia, part of the company’s AI for Social Good program. The project team is exploring ways to improve speech recognition for people who are deaf or have neurological conditions such as ALS, stroke, Parkinson’s, multiple sclerosis or traumatic brain injury.

Google has partnered with nonprofit organizations ALS Therapy Development Institute and ALS Residence Initiative (ALSRI) to collect recorded voice samples from people who have the neurodegenerative disease, one that often leads to severe speech and mobility difficulties.

For those with neurological conditions, voice-activated systems can play a key role in completing everyday tasks and conversing with loved ones, caregivers or colleagues. “You can turn on your lights, your music or communicate with someone. But this only works if the technology can actually recognize your voice and transcribe it,” says Julie Cattiau, a product manager at Google AI.

The company’s speech recognition technology utilizes machine learning algorithms that require extensive data training. “We have hundreds of thousands, or even millions, of sentences that people have read—and we use them as examples for the algorithms to learn how to recognize each,” says Cattiau. “But it’s not enough for people with disabilities.”

With Project Euphonia, the team will instead use voice samples from people who have impaired speech in the hope that the underlying system will be trained to understand inarticulate commands.

While the goal is to create technology that is more accessible for people with speech impediments, the end result is still unclear.

“It’s possible that we will have models that work for multiple people with ALS and other medical conditions,” says Cattiau. “It’s also possible that people, even just within ALS, sound too different to have such a machine learning model in place. And in that case, we may need to have a level of personalization so that each person has their own model.”

Google’s speech recognition technology can comprehend virtually any voice command for people without speech impairments, due to the large data set that has been available for training. But some uncertainty exists about how broadly speech technology will be able to understand and act on directives from those who have difficulty speaking. The Project Euphonia team has only a limited number  of voice samples from people with speech impediments, which allows it to focus only on specific-use words and phrases such as “read me a book” or “turn off the lights.”

Though Cattiau’s team has collected tens of thousands of recorded phrases, she says it needs hundreds of thousands more. That’s partly why Google CEO Sundar Pichai unveiled this project at the company’s annual developer conference in May.

“We are working hard to provide these voice-recognition models to the Google Assistant in the future,” he said, calling on people with slurred and impaired speech to submit their voice samples.

“Impaired speech is a very difficult data set to put together. It’s not as simple as asking people to record phrases, and there’s no data set just lying around,” Cattiau says. “We have to first put it together, and that’s a lot of work.”

Perhaps the most groundbreaking of Project Euphonia’s initiatives is its work on new interactive AI systems for people who are completely nonverbal. Also in its early stages, these systems are being trained to detect gestures, vocalizations and facial expressions, which can then trigger certain actions like sending or reading a text message.

“We want to cover the full spectrum of people—and not only those who can still speak,” says Cattiau. Although Project Euphonia is still in its infancy, it could eventually have a great impact on those with disabilities, giving them the freedom and flexibility to live independently.Follow me on Twitter.

-Ruth Umoh; Forbes Staff

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Nigeria Needs A More Effective Sanitation Strategy Here Are Some Ideas:

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In November last year, Nigeria declared that its water supply, sanitation and hygiene sector was in crisis. This was partly prompted by the fact that the country has struggled to make progress towards ending open defecation.

Almost one in four Nigerians – around 50 million people – defecates in open areas. They do so because access to proper sanitation, like private indoor toilets or outdoor communal toilets, has not improved in recent years.

In fact, it’s got worse: in 2000, 36.5% of Nigerians had access to sanitation facilities that hygienically separate human excreta from human contact. By 2015 the figure had dropped to 32.6%, likely driven by rapid population growth and a lack of sufficient private and public investment.

Open defecation comes with many risks. It can lead to waterborne diseases, cause preventable deaths, and hamper education and economic growth. It also infringes on people’s privacy and dignity.

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The government has tried several strategies to address this problem. In 2008 it adopted an intervention called “Community Led Total Sanitation”. This is a community-level intervention aimed at reducing open defecation and improving toilet coverage.

It draws in community leaders and ordinary residents so they can understand the risks associated with open defecation. By 2014 the intervention was deployed in all 36 Nigerian states, covering around 16% of the country’s 123,000 communities.

We wanted to know how effective the programme has been, if at all. So we conducted a study and found that community-led total sanitation programmes alone will not eradicate the practice of open defecation. But they could be part of the solution.

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We found that the programme currently works quite well in poor communities but is less effective in richer places – that is, places with higher average ownership rates of assets such as fridges, motorcycles, TVs, smartphones and power generators.

Poorer communities distinguish themselves from richer ones in other ways, too. They tend to have higher levels of trust among their citizens, lower initial levels of toilet coverage and lower wealth inequality. But none of these characteristics is, on its own, as strong a predictor of where the intervention works better than community wealth.

Low community wealth is a simple measure that encompasses all these different features, and is associated with greater programme effectiveness.

The intervention

Community-led total sanitation typically starts with mobilisation. This initially involves community leaders and then, through them, communities more broadly. Then, a community meeting is held at which residents typically start by marking their household’s location and toilet ownership status on a stylised map on the ground. They also identify and mark regular open defecation sites.

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Facilitators use the map to trace the community’s contamination paths of human faeces into water supplies and food. A number of other activities may follow, such as walks through the community that are often referred to as “walks of shame” during which visible faeces are pointed out, to evoke further disgust and shame.

Another common activity involves calculating medical expenses related to illnesses that are caused by open defecation practices.

The research

In 2015 we worked with the charity organisation WaterAid Nigeria and local government agencies in the states of Ekiti and Enugu to design a field experiment in areas with no recent experience of community led total sanitation, or similar interventions.

The community-led total sanitation programme was implemented in a random sample of 125 out of 247 clusters of rural communities.

To study the intervention’s effectiveness, we interviewed 20 randomly selected households before community-led total sanitation took place. We followed up with these households eight, 24 and 32 months after the intervention.

We found that the programme’s roll-out didn’t lead to any changes in sanitation practices in richer communities. But it worked in the poorest communities. The prevalence of open defecation declined by an average of nine percentage points in poorer communities when compared to other poor areas where the programme wasn’t implemented. This drop was accompanied by a similar increase in toilet ownership rates.

Impact depends on wealth

Our results are in line with observations by the designers of the programme. But we are the first to show quantitatively that community asset wealth is a good predictor of whether the intervention can be expected to be successful. Unfortunately, our data does not allow us to pin down why households in poorer communities are more susceptible to the programme. However, these results have important implications for more cost effective targeting of the programme.

Most countries, including Nigeria, have access to readily available datafrom household surveys that can be used to measure how asset-poor a community is. These data can be used to identify and target communities where community-led total sanitation is likely to have the biggest impact.

Eradicating open defecation is not just a Nigerian priority. Today, an estimated 4.5 billion people globally don’t have access to safe sanitation. So we also looked at data and research about this same intervention from other parts of the world.

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Community-led total sanitation intervention was first developed in Bangladesh in 1999. It has now been implemented in more than 25 Latin American, Asian and African countries.

We used information from evaluations of this intervention in Mali, India, Tanzania, Bangladesh and Indonesia. The studies found widely differing impacts. These ranged from a 30 percentage point increase in toilet ownership in Mali to no detectable impact on toilet ownership in Bangladesh.

Using a measure of wealth for these countries, we found that sanitation interventions have larger impacts in poorer areas, such as Tanzania, and low or no impact in relatively richer areas, such as Indonesia. This supports the idea that targeting poorer areas maximises the impact of community led total sanitation.

Conclusion

Our research shows that while community-led total sanitation is effective in Nigeria’s poorer areas, there are two main challenges.

First, community-led total sanitation had no perceivable impact in the wealthier half of our sample. There, open defecation remains widespread. And second, even in poor areas, a large number of households still engaged in open defecation after the intervention.

This suggests that while community-led total sanitation can be better targeted, it needs to be complemented with other policies – subsidies, micro-finance or programmes that promote private sector activity in this under-served market.

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