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Autor Tópico: Tesla (TSLA) - Tópico principal  (Lida 233679 vezes)

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #80 em: 2015-10-26 13:55:07 »
Olhar para "este momento" não faz sentido. "Este momento" só existe porque a Tesla tomou uma opção que ainda não foi tomada pelos outros, mas que os outros não estão impedidos de tomar. Para "este momento" não existe dúvida de que a Tesla tem algo que os outros não têm, mas o que é crucial é que o que a Tesla tem os outros não estão impedidos de ter.

A Tesla não está avaliada com base neste momento, e sim nos próximos 50 anos.

Esta é uma análise que se tem que fazer para qualquer empresa.

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O custo não é uma barreira de entrada para uma indústria lucrativa. Além de que o custo de entrar nos EVs é mínimo para a escala dos outros fabricantes de automóveis.

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Eu já olhei para muitas das patentes da Tesla e não vi nada de impeditivo para os restantes players. A Panasonic pode vender (e vende) as baterias a quem quiser. A MBLY pode vender (e vende) a tecnologia de ajuda à condução a quem quiser. E por aí adiante.

A infraestrutura é irrelevante porque pode ser integralmente reproduzida em 6 meses a 1 ano.

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Essencialmente a posição que tomas e que muitos dos seguidores da Tesla tomam não faz sentido com base no conhecimento de mercados que existe disponível.

Isto é uma situação similar à que existia no ferro (iron ore). O pessoal positivo no sector avançava com argumentos iguais, que era muito difícil abrir uma mina, etc, e eu expliquei com os mesmos argumentos que estou a usar aqui: que havendo retorno, as minas apareceriam, nem que demorasse algum tempo. O resultado óbvio é que o ferro colapsou e os retornos em excesso desapareceram. Na realidade a maior defesa que a TSLA tem é que ainda não tem lucros, mas isso não é lá muito positivo.
« Última modificação: 2015-10-26 14:00:34 por Incognitus »
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

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McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #81 em: 2015-10-26 14:04:16 »
Não consigo concordar contigo no aspecto de que não faz sentido avaliar a situação no tempo.

As avaliações fazem-se sempre "no tempo" - no actual e no futuro.

No actual, avalia-se as vantagens que uma dada empresa possui em relação às outras.

No futuro, avalia-se as expectativas e a probabilidade que uma determinada empresa tem em ser mais competitiva e ganhar quota de mercado (via alcançar mais vantagens que as outras).

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Qualquer "barreira" tem um custo e é esse custo que define se o investimento associado vale a pena ou não para ganhar uma determinada vantagem competitiva.

isto é dos "livros"...

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Re: Tesla (TSLA) - Tópico principal
« Responder #82 em: 2015-10-26 14:09:52 »
Não penso que estejas aberto a compreender a problemática.

As vantagens sustentáveis são aquelas que permitem manter um retorno em excesso. A Tesla nem tem retorno em excesso, e pior ainda, não tem vantagens sustentáveis sequer para manter o que tem neste momento. O que isso significa é que quando entrar concorrência directa no mercado, a Tesla irá ver margens ainda piores e não terá certeza nenhuma de ser a vencedora na batalha.

As barreiras á entrada são coisas que impedem ou tornam não-económica a entrada num mercado. O custo não é uma delas, pelo contrário. Se um mercado promete um retorno de 20% com um custo de entrada elevado, isso só significa que se consegue aplicar muito capital a 20%, o que até o torna mais atraente. O montante de capital:
* Não é uma barreira.
* Nem é elevado no caso dos EVs, tendo em conta a dimensão relativa dos outros fabricantes de automóveis.

Para se ver que o custo não é uma barreira, o ferro era um bom exemplo, uma nova mína custava biliões de dólares, e dado o retorno isso não impediu novas minas de aparecerem. Porque havia retorno. É esta entrada de concorrentes que depois elimina o retorno excessivo.

Isto são coisas dos livros, tens razão. É como o mercado funciona, e isto não é nada favorável à Tesla. A principal possível vantagem sustentável da Tesla é a sua marca, mas nisso não ajuda que esteja a ser rotulada como tendo fiabilidade abaixo da média (como eu previ e agora a Consumer Reports confirmou).
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #83 em: 2015-10-26 14:34:58 »
Mas também estás a partir do pressuposto que a Tesla ficará estática durante todo o tempo enquanto esses novos concorrentes não chegam ao mercado.

O que não é verdade.

Não consigo adivinhar o futuro, mas é fácil de imaginar que a Tesla irá continuar a criar e a fazer cada vez mais, e que isso irá colocar (ainda) mais desafios à concorrência.

Quando essa concorrência chegar, o cenário já será completamente diferente.


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Em relação ao "custo". O que descreves, eu chamo-lhe "valor". É claro que se um mercado tiver um valor de oportunidade elevado, o custo do investimento é avaliado relativamente a esse potencial. O custo até pode ser de 1 MM se o ROI for de 50 MM...

Concordamos.

Mas o que referi é diferente, eu não dei o exemplo do "custo" como sendo ele próprio uma barreira em si. Eu apenas referi que cada barreira têm um determinado custo associado e que na avaliação de investimento da concorrência, isso é também tomado em consideração.

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #84 em: 2015-10-26 14:38:32 »
Não estou a prever que a Tesla fica estática. Entre aqui e os outros entrarem, as margens da TSLA deveriam melhorar -- mas partem negativas ... depois pioram quando os outros entrarem.

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Não vejo qualquer barreira à entrada dos outros concorrentes ... nem custo nem outra.

"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

Lark

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Re: Tesla (TSLA) - Tópico principal
« Responder #85 em: 2015-11-04 17:22:51 »
LG Chem, Tesla tie-up could jolt Panasonic

SEOUL -- South Korea's LG Chem is in the final stage of negotiations to supply lithium-ion batteries to U.S. electric vehicle maker Tesla Motors, which has until now sourced the key component almost exclusively from Panasonic.

     This could deal a major blow to the Japanese electronics giant, which positions the automotive business as a growth pillar, because now it will be exposed to competition in serving a key customer.

     Panasonic currently produces the electric-vehicle batteries for Tesla in Osaka Prefecture. The two companies are also building a massive battery plant in the U.S. state of Nevada. The $5 billion facility will be completed in 2020, with a portion of the plant to go online next year.

     Panasonic is the global leader in automotive lithium-ion batteries, with a 46% market share, followed by 17% for Automotive Energy Supply -- a joint venture of Nissan Motor and NEC -- according to research company Techno Systems Research. LG Chem comes in third with a share of 11%.

     But LG Chem supplies to more than 20 companies, including General Motors and Renault, and delivery under many contracts has yet to go into full swing.

     On Tuesday, a new LG Chem facility was completed in Nanjing, China, becoming the company's third battery plant after sites in South Korea and the U.S. Combined annual production capacity has increased 40% to the equivalent of more than 180,000 electric vehicles.

     LG Chem's battery business, including mobile phone batteries, generated sales of 2.85 trillion won ($2.55 billion) last year.

     By adding LG Chem as a source, Tesla apparently seeks to stabilize battery supply and spur competition for better pricing and product performance.

     To increase production of the high-end Model S sedan and the Model X sport utility vehicle, Tesla is working to expand its production capacity in California to over 50,000 vehicles annually by the end of the year, up from 35,000 at the start of 2015. Separately, the company's second plant opened in September in the Netherlands. So Tesla's global capacity will grow to nearly 100,000 units. To put this figure into perspective, the world's best-selling electric vehicle, the Nissan Leaf, sold 60,000 units last year.

Tesla's move symbolizes the intensifying competition Japanese manufacturers face from the Koreans. In liquid crystal displays and memory chips, Samsung Electronics, LG Electronics and other Korean manufacturers have surpassed Japanese companies. In 2011, the combined market share of South Korean manufacturers in lithium-ion batteries, including those for mobile phones, topped that of Japanese companies.

     The automotive area has remained a strength of Japanese companies because the country's automakers have led in hybrids and electric vehicles. Nissan buys batteries for the Leaf from the joint venture Automotive Energy Supply, while Toyota Motor gets nickel-hydrogen batteries for its Prius hybrids from within the group.

     As non-Japanese automakers beef up their hybrid and electric-vehicle offerings, competition from Korean companies and other battery makers likely will intensify.

     Tesla is an important customer because its vehicles require many batteries to travel long distances between charges, and the company is enjoying sales growth despite lofty prices on some products.

     In light of the Volkswagen emissions scandal, electric cars are drawing fresh attention as green vehicles. Battery performance is key to determining vehicle pricing and driving ranges, so suppliers are actively developing better technologies.

fonte
Be Kind; Everyone You Meet is Fighting a Battle.
Ian Mclaren
------------------------------
If you have more than you need, build a longer table rather than a taller fence.
l6l803399
-------------------------------------------
So, first of all, let me assert my firm belief that the only thing we have to fear is...fear itself — nameless, unreasoning, unjustified terror which paralyzes needed efforts to convert retreat into advance.
Franklin D. Roosevelt

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #86 em: 2015-11-04 17:37:18 »
Ontem foram apresentados os resultados do terceiro trimestre - 2015-Q3:

Tesla Motors Third Quarter 2015 Summary:
• Model X launch & start of deliveries
• Autopilot released to 40,000 vehicles globally, over the air
• Produced a record 13,091 vehicles, despite one week shut down
• Delivered a record 11,603 new vehicles
• Gigafactory construction and production ahead of schedule
• Model 3 unveiling planned for late March 2016

- In Q3, global Model S orders increased by more than 50% from a year ago, and grew at a faster pace in North America, Europe and Asia, than during Q2.

- We are seeing very strong demand for Tesla Energy products globally, and particularly in Australia, Germany and South Africa.

- In Q3, we exceeded our plan by producing 13,091 vehicles, despite a one-week shut down to expand manufacturing capacity and delivered 11,603 vehicles, slightly above the number estimated in our October announcement.;

- Cash and cash equivalents were $1.4 billion at the end of the quarter. Capital expenditures were primarily for the capacity expansion and tooling associated with Model X, as well as for the construction of the Gigafactory.

- In Q4, we plan to build 15,000 to 17,000 vehicles, and deliver 17,000 to 19,000 vehicles, which will result in 50,000 to 52,000 total deliveries for the year.

- Looking ahead, we still remain highly confident of average production and deliveries of 1,600 to 1,800 vehicles per week for Model S and Model X combined during 2016.

- We plan to invest about $500 million in Q4, which will bring the projected total capital expenditures for this year to about $1.7 billion. The increase in spending is primarily due to accelerated investments in the Gigafactory, further vertical integration of seat assembly and other manufacturing activities, as well as faster milestone execution by certain suppliers for Model X manufacturing equipment and tooling.

- Our customers drove their cars almost 250 million miles this quarter, for a total of nearly 1.5 billion miles to date.

http://files.shareholder.com/downloads/ABEA-4CW8X0/961381394x0x858516/F50A9FAF-BA73-4263-8E16-DE1FAC0BABDF/Q3_15_Shareholder_Letter.pdf

Lark

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Re: Tesla (TSLA) - Tópico principal
« Responder #87 em: 2015-11-04 17:39:07 »
How Uber’s Autonomous Cars Will Destroy 10 Million Jobs and Reshape the Economy by 2025

I have spent quite a bit of time lately thinking about autonomous cars, and I wanted to summarize my current thoughts and predictions. Most people – experts included – seem to think that the transition to driverless vehicles will come slowly over the coming few decades, and that large hurdles exist for widespread adoption. I believe that this is significant underestimation. Autonomous cars will be commonplace by 2025 and have a near monopoly by 2030, and the sweeping change they bring will eclipse every other innovation our society has experienced. They will cause unprecedented job loss and a fundamental restructuring of our economy, solve large portions of our environmental problems, prevent tens of thousands of deaths per year, save millions of hours with increased productivity, and create entire new industries that we cannot even imagine from our current vantage point.

The transition is already beginning to happen. Elon Musk, Tesla Motor’s CEO, says that their 2015 models will be able to self-drive 90 percent of the time.1 And the major automakers aren’t far behind – according to Bloomberg News, GM’s 2017 models will feature “technology that takes control of steering, acceleration and braking at highway speeds of 70 miles per hour or in stop-and-go congested traffic.”2 Both Google3 and Tesla4 predict that fully-autonomous cars – what Musk describes as “true autonomous driving where you could literally get in the car, go to sleep and wake up at your destination” – will be available to the public by 2020.

How it will unfold

Industry experts think that consumers will be slow to purchase autonomous cars – while this may be true, it is a mistake to assume that this will impede the transition. Morgan Stanley’s research shows that cars are driven just 4% of the time,5 which is an astonishing waste considering that the average cost of car ownership is nearly $9,000 per year.6 Next to a house, an automobile is the second most expensive asset that most people will ever buy – it is no surprise that ride sharing services like Uber and car sharing services like Zipcar are quickly gaining popularity as an alternative to car ownership. It is now more economical to use a ride sharing service if you live in a city and drive less than 10,000 miles per year.7 The impact on private car ownership is enormous: a UC-Berkeley study showed that vehicle ownership among car sharing users was cut in half.8 The car purchasers of the future will not be you and me – cars will be purchased and operated by ride sharing and car sharing companies.

And current research confirms that we would be eager to use autonomous cars if they were available. A full 60% of US adults surveyed stated that they would ride in an autonomous car, and nearly 32% said they would not continue to drive once an autonomous car was available instead.10  But no one is more excited than Uber – drivers take home at least 75% of every fare.11 It came as no surprise when CEO Travis Kalanick recently stated that Uber will eventually replace all of its drivers with self-driving cars.

A Columbia University study suggested that with a fleet of just 9,000 autonomous cars, Uber could replace every taxi cab in New York City – passengers would wait an average of 36 seconds for a ride that costs about $0.50 per mile. Such convenience and low cost will make car ownership inconceivable, and autonomous, on-demand taxis – the ‘transportation cloud’ – will quickly become dominant form of transportation – displacing far more than just car ownership, it will take the majority of users away from public transportation as well. With their $41 billion valuation,15 replacing all 171,000 taxis16  in the United States is well within the realm of feasibility – at a cost of $25,000 per car, the rollout would cost a mere $4.3 billion.

Fallout

The effects of the autonomous car movement will be staggering. PricewaterhouseCoopers predicts that the number of vehicles on the road will be reduced by 99%, estimating that the fleet will fall from 245 million to just 2.4 million vehicles.

Disruptive innovation does not take kindly to entrenched competitors – like Blockbuster, Barnes and Noble, Polaroid, and dozens more like them, it is unlikely that major automakers like General Motors, Ford, and Toyota will survive the leap. They are geared to produce millions of cars in dozens of different varieties to cater to individual taste and have far too much overhead to sustain such a dramatic decrease in sales. I think that most will be bankrupt by 2030, while startup automakers like Tesla will thrive on a smaller number of fleet sales to operators like Uber by offering standardized models with fewer options.

Ancillary industries such as the $198 billion automobile insurance market, $98 billion automotive finance market, $100 billion parking industry, and the $300 billion automotive aftermarket will collapse as demand for their services evaporates. We will see the obsolescence of rental car companies, public transportation systems, and, good riddance, parking and speeding tickets. But we will see the transformation of far more than just consumer transportation: self-driving semis, buses, earth movers, and delivery trucks will obviate the need for professional drivers and the support industries that surround them.

The Bureau of Labor Statistics lists that 884,000 people are employed in motor vehicles and parts manufacturing, and an additional 3.02 million in the dealer and maintenance network. Truck, bus, delivery, and taxi drivers account for nearly 6 million professional driving jobs. Virtually all of these 10 million jobs will be eliminated within 10-15 years, and this list is by no means exhaustive.

But despite the job loss and wholesale destruction of industries, eliminating the needs for car ownership will yield over $1 trillion in additional disposable income – and that is going to usher in an era of unprecedented efficiency, innovation, and job creation.

A view of the future

Morgan Stanley estimates that a 90% reduction in crashes would save nearly 30,000 lives and prevent 2.12 million injuries annually. Driverless cars do not need to park – vehicles cruising the street looking for parking spots account for an astounding 30% of city traffic, not to mention that eliminating curbside parking adds two extra lanes of capacity to many city streets. Traffic will become nonexistent, saving each US commuter 38 hours every year – nearly a full work week. As parking lots and garages, car dealerships, and bus stations become obsolete, tens of millions of square feet of available prime real estate will spur explosive metropolitan development.

The environmental impact of autonomous cars has the potential to reverse the trend of global warming and drastically reduce our dependence on fossil fuels. Passenger cars, SUVs, pickup trucks, and minivans account for 17.6% of greenhouse gas emissions – a 90% reduction of vehicles in operation would reduce our overall emissions by 15.9%. As most autonomous cars are likely to be electric, we would virtually eliminate the 134 billion of gasoline used each year in the US alone. And while recycling 242 million vehicles will certainly require substantial resources, the surplus of raw materials will decrease the need for mining.

But perhaps most exciting for me are the coming inventions, discoveries, and creation of entire new industries that we cannot yet imagine.

I dream of the transportation cloud: near-instantly available, point-to-point travel. Ambulances that arrive to the scene within seconds. A vehicle-to-grid distributed power system. A merging of city and suburb as commuting becomes fast and painless. Dramatically improved mobility for the disabled. On-demand rental of nearly anything you can imagine. The end of the DMV!

It is exciting to be alive, isn’t it?

zack kanter
Be Kind; Everyone You Meet is Fighting a Battle.
Ian Mclaren
------------------------------
If you have more than you need, build a longer table rather than a taller fence.
l6l803399
-------------------------------------------
So, first of all, let me assert my firm belief that the only thing we have to fear is...fear itself — nameless, unreasoning, unjustified terror which paralyzes needed efforts to convert retreat into advance.
Franklin D. Roosevelt

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #88 em: 2015-11-04 17:48:28 »
LG Chem, Tesla tie-up could jolt Panasonic

Este contrato é para adquirir baterias para suportar o upgrade de baterias para os antigos Roadsters. Ao que parece a Panasonic não consegue fornecer mais à Tesla sem afectar os restantes contratos que possui.

Por isso a Tesla, enquanto a GF não começar a produzir, não teve outro remédio que virar-se para os outros players. A LG Chem foi a escolhida.

Mas deverá ser uma quantidade limitada e um contrato pequeno.


Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #89 em: 2015-11-04 18:37:41 »
Notes On The Tesla Q3 2015 Earnings Report
http://seekingalpha.com/article/3640986-notes-on-the-tesla-q3-2015-earnings-report

Três principais notas:
* A TSLA manteve o nível mais baixo da sua guidance para vendas em 2015, mas desceu o nível mais elevado do intervalo. Eu acho que a TSLA só não baixou o nível mais baixo para comprar tempo -- porque na realidade vai falhar a sua estimativa mais baixa. Uma incógnita é apenas quantos carros serão vendidos na Dinamarca no último trimestre, pois os impostos lá sobem tanto em Janeiro de 2016 que o país pode surpreender com a venda de 1000-2000 carros num mercado pequeno num só trimestre.
* A TSLA está a queimar dinheiro mais rápido do que era de esperar e guiou para queimar mais do que o esperado no último trimestre, também. Isto signica que não obstante ter recentemente obtido financiamento e emitido $800 milhões em acções, parece que no final do 1º trimestre de 2016 já estará a precisar de mais dinheiro.
* A noção de que está a ver procura acrescida (como a TSLA diz) não faz sentido, se considerarmos que as vendas no 3º timestre foram flat com o trimestre anterior, e os depósitos de clientes até cairam. Isto basicamente é incompatível com procura (encomendas) crescentes no trimestre.

Por fim, a acção subir não surpreende -- o mercado subiu verticalmente até máximos enquanto a TSLA não o acompanhou durante semanas, provavelmente o trade curto já estava "crowded" quando chegou aos resultados.
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #90 em: 2015-11-04 18:39:59 »
How Uber’s Autonomous Cars Will Destroy 10 Million Jobs and Reshape the Economy by 2025

I have spent quite a bit of time lately thinking about autonomous cars, and I wanted to summarize my current thoughts and predictions. Most people – experts included – seem to think that the transition to driverless vehicles will come slowly over the coming few decades, and that large hurdles exist for widespread adoption. I believe that this is significant underestimation. Autonomous cars will be commonplace by 2025 and have a near monopoly by 2030, and the sweeping change they bring will eclipse every other innovation our society has experienced. They will cause unprecedented job loss and a fundamental restructuring of our economy, solve large portions of our environmental problems, prevent tens of thousands of deaths per year, save millions of hours with increased productivity, and create entire new industries that we cannot even imagine from our current vantage point.

The transition is already beginning to happen. Elon Musk, Tesla Motor’s CEO, says that their 2015 models will be able to self-drive 90 percent of the time.1 And the major automakers aren’t far behind – according to Bloomberg News, GM’s 2017 models will feature “technology that takes control of steering, acceleration and braking at highway speeds of 70 miles per hour or in stop-and-go congested traffic.”2 Both Google3 and Tesla4 predict that fully-autonomous cars – what Musk describes as “true autonomous driving where you could literally get in the car, go to sleep and wake up at your destination” – will be available to the public by 2020.

How it will unfold

Industry experts think that consumers will be slow to purchase autonomous cars – while this may be true, it is a mistake to assume that this will impede the transition. Morgan Stanley’s research shows that cars are driven just 4% of the time,5 which is an astonishing waste considering that the average cost of car ownership is nearly $9,000 per year.6 Next to a house, an automobile is the second most expensive asset that most people will ever buy – it is no surprise that ride sharing services like Uber and car sharing services like Zipcar are quickly gaining popularity as an alternative to car ownership. It is now more economical to use a ride sharing service if you live in a city and drive less than 10,000 miles per year.7 The impact on private car ownership is enormous: a UC-Berkeley study showed that vehicle ownership among car sharing users was cut in half.8 The car purchasers of the future will not be you and me – cars will be purchased and operated by ride sharing and car sharing companies.

And current research confirms that we would be eager to use autonomous cars if they were available. A full 60% of US adults surveyed stated that they would ride in an autonomous car, and nearly 32% said they would not continue to drive once an autonomous car was available instead.10  But no one is more excited than Uber – drivers take home at least 75% of every fare.11 It came as no surprise when CEO Travis Kalanick recently stated that Uber will eventually replace all of its drivers with self-driving cars.

A Columbia University study suggested that with a fleet of just 9,000 autonomous cars, Uber could replace every taxi cab in New York City – passengers would wait an average of 36 seconds for a ride that costs about $0.50 per mile. Such convenience and low cost will make car ownership inconceivable, and autonomous, on-demand taxis – the ‘transportation cloud’ – will quickly become dominant form of transportation – displacing far more than just car ownership, it will take the majority of users away from public transportation as well. With their $41 billion valuation,15 replacing all 171,000 taxis16  in the United States is well within the realm of feasibility – at a cost of $25,000 per car, the rollout would cost a mere $4.3 billion.

Fallout

The effects of the autonomous car movement will be staggering. PricewaterhouseCoopers predicts that the number of vehicles on the road will be reduced by 99%, estimating that the fleet will fall from 245 million to just 2.4 million vehicles.

Disruptive innovation does not take kindly to entrenched competitors – like Blockbuster, Barnes and Noble, Polaroid, and dozens more like them, it is unlikely that major automakers like General Motors, Ford, and Toyota will survive the leap. They are geared to produce millions of cars in dozens of different varieties to cater to individual taste and have far too much overhead to sustain such a dramatic decrease in sales. I think that most will be bankrupt by 2030, while startup automakers like Tesla will thrive on a smaller number of fleet sales to operators like Uber by offering standardized models with fewer options.

Ancillary industries such as the $198 billion automobile insurance market, $98 billion automotive finance market, $100 billion parking industry, and the $300 billion automotive aftermarket will collapse as demand for their services evaporates. We will see the obsolescence of rental car companies, public transportation systems, and, good riddance, parking and speeding tickets. But we will see the transformation of far more than just consumer transportation: self-driving semis, buses, earth movers, and delivery trucks will obviate the need for professional drivers and the support industries that surround them.

The Bureau of Labor Statistics lists that 884,000 people are employed in motor vehicles and parts manufacturing, and an additional 3.02 million in the dealer and maintenance network. Truck, bus, delivery, and taxi drivers account for nearly 6 million professional driving jobs. Virtually all of these 10 million jobs will be eliminated within 10-15 years, and this list is by no means exhaustive.

But despite the job loss and wholesale destruction of industries, eliminating the needs for car ownership will yield over $1 trillion in additional disposable income – and that is going to usher in an era of unprecedented efficiency, innovation, and job creation.

A view of the future

Morgan Stanley estimates that a 90% reduction in crashes would save nearly 30,000 lives and prevent 2.12 million injuries annually. Driverless cars do not need to park – vehicles cruising the street looking for parking spots account for an astounding 30% of city traffic, not to mention that eliminating curbside parking adds two extra lanes of capacity to many city streets. Traffic will become nonexistent, saving each US commuter 38 hours every year – nearly a full work week. As parking lots and garages, car dealerships, and bus stations become obsolete, tens of millions of square feet of available prime real estate will spur explosive metropolitan development.

The environmental impact of autonomous cars has the potential to reverse the trend of global warming and drastically reduce our dependence on fossil fuels. Passenger cars, SUVs, pickup trucks, and minivans account for 17.6% of greenhouse gas emissions – a 90% reduction of vehicles in operation would reduce our overall emissions by 15.9%. As most autonomous cars are likely to be electric, we would virtually eliminate the 134 billion of gasoline used each year in the US alone. And while recycling 242 million vehicles will certainly require substantial resources, the surplus of raw materials will decrease the need for mining.

But perhaps most exciting for me are the coming inventions, discoveries, and creation of entire new industries that we cannot yet imagine.

I dream of the transportation cloud: near-instantly available, point-to-point travel. Ambulances that arrive to the scene within seconds. A vehicle-to-grid distributed power system. A merging of city and suburb as commuting becomes fast and painless. Dramatically improved mobility for the disabled. On-demand rental of nearly anything you can imagine. The end of the DMV!

It is exciting to be alive, isn’t it?

zack kanter


A Tesla não é um factor nos carros autónomos. As ajudas ao condutor que a Tesla possuí são as disponibilizadas pela MobilEye, e nem consta que a Tesla possua investigação relevante no domínio de carros autónomos (excepto na imaginação do povo).
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #91 em: 2015-11-04 22:04:52 »
Notes On The Tesla Q3 2015 Earnings Report
http://seekingalpha.com/article/3640986-notes-on-the-tesla-q3-2015-earnings-report

Três principais notas:
* A TSLA manteve o nível mais baixo da sua guidance para vendas em 2015, mas desceu o nível mais elevado do intervalo. Eu acho que a TSLA só não baixou o nível mais baixo para comprar tempo -- porque na realidade vai falhar a sua estimativa mais baixa. Uma incógnita é apenas quantos carros serão vendidos na Dinamarca no último trimestre, pois os impostos lá sobem tanto em Janeiro de 2016 que o país pode surpreender com a venda de 1000-2000 carros num mercado pequeno num só trimestre.
* A TSLA está a queimar dinheiro mais rápido do que era de esperar e guiou para queimar mais do que o esperado no último trimestre, também. Isto signica que não obstante ter recentemente obtido financiamento e emitido $800 milhões em acções, parece que no final do 1º trimestre de 2016 já estará a precisar de mais dinheiro.
* A noção de que está a ver procura acrescida (como a TSLA diz) não faz sentido, se considerarmos que as vendas no 3º timestre foram flat com o trimestre anterior, e os depósitos de clientes até cairam. Isto basicamente é incompatível com procura (encomendas) crescentes no trimestre.

Por fim, a acção subir não surpreende -- o mercado subiu verticalmente até máximos enquanto a TSLA não o acompanhou durante semanas, provavelmente o trade curto já estava "crowded" quando chegou aos resultados.


Sim, eu gostei de ler esse artigo.

Mas, tenho os seguintes comentários :

- Eu acho que é possível que a TSLA consiga fazer os 50k de unidades vendidas em 2015, se pensarmos não só na situação possível da Dinamarca, mas também pelo facto da TSLA:
    * Ter feito o upgrade da linha de montagem em Agosto e já conseguir produzir cada vez mais carros por dia
    * Por aparentemente não ter havido (ainda) uma grande canibalização do TMS
    * O pipeline do TMX é suficientemente grande neste momento para escoar tudo o que se produzir.
    * Assim que conseguirem resolverem os problemas dos assentos traseiros e do selante das portas, o ramp up do TMX será muito rápido (devido ao tal upgrade que fizeram para dar mais capacidade à fábrica) e chegar às "algumas centenas por semana"
    * Porque já tem cerca de 1500 unidades em inventário prontas a sair no Q4

- O "Burn-in", é como já referi anteriormente, a TSLA é uma startup não é uma empresa madura e consolidada, logo é expectável que faça agora os investimentos que conseguir para preparar melhor o seu futuro. E são várias as batalhas que tem. Ainda por cima agora, com o desenvolvimento do TM3 e pela critica necessidade da GF para o conseguir produzir. Neste momento não tenho grandes duvidas que qualquer $$ que a TSLA pedir os accionistas irão dar sem pestanejar.

Muito honestamente, prefiro que a TSLA peça mais $1Bi aos seus accionistas já no próximo Trimestre mas produza o TM3 como realmente pretende e que seja o melhor carro possível do que não peça nada, tenha FCF positivo e depois decepcione com o resultado.

- Relativamente à procura. Por um lado acho que aquilo que se vê é que a TSLA tem algumas limitações pelo lado da produção (isso deverá melhorar em 2016) e por outro acho que a TSLA está a fazer bem as coisas pelo lado do mercado. É preciso tempo para os mercados novos amadurecerem e a marca fixar-se. É preciso colocar lojas, service centers e os supercarregadores primeiro e o resto vem a depois.
« Última modificação: 2015-11-04 22:06:20 por McKricas »

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #92 em: 2015-11-05 00:31:13 »
Naturalmente que ainda não há canibalização ... ainda não há Modelo X.

A TSLA não tinha dificuldade em produzir mais, tem produzido consistentemente mais, já fez alguns 9000 carros a mais do que os que alguma vez entregou ... não são 1500, são alguns 9000.

Sim, o Modelo X durante algum tempo terá encomendas de trás significativas, mas muitas vão ser canceladas porque o modelo mais barato durante algum tempo custará >$93,000.
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #93 em: 2015-11-05 11:14:04 »
Naturalmente que ainda não há canibalização ... ainda não há Modelo X.

A TSLA não tinha dificuldade em produzir mais, tem produzido consistentemente mais, já fez alguns 9000 carros a mais do que os que alguma vez entregou ... não são 1500, são alguns 9000.

Sim, o Modelo X durante algum tempo terá encomendas de trás significativas, mas muitas vão ser canceladas porque o modelo mais barato durante algum tempo custará >$93,000.

Sim, mas poderia haver (pelo menos a percepção) de que as encomendas do TMS reduzissem em favor do TMX. Não me parece que isso tenha ocorrido. O valor das reservas, embora global, é apenas um pouco inferior às reservas no Q2.

E na verdade o TMS e o TMX são 2 produtos diferentes que visam atacar o mesmo segmento de mercado, portanto mesmo que exista canibalização, não penso que isso seja um problema muito grande para a TSLA.

O TMS/TMX irá acabar por resumir-se a uma questão de preferencia para o cliente deste mercado (e não de preço).

Não conheço esse nº de 9000 carros a mais. Baseas-te no valor do inventário ? atenção que nesse valor também estão considerado os carros do CPO, carros de serviço, demonstração, etc etc.

Mas é um facto conhecido que o upgrade à fábrica em Agosto foi para aumentar a capacidade de produção. E isso já se nota nos nºs de carros produzidos neste Q3. Mesmo com uma semana parada a fábrica produziu um total de 13.091 unidades, mais do que os 12.807 no Q2. E já nesse Q2 o aumento da produção em relação ao Q1 foi de 15%.

Por isso é que não me parece muito complicado chegar ao fim do Q4 e produzir os 15000 que faltam para alcançar os 50000. É apenas passar dos cerca de 240/dia para 250/dia (cerca de 14.5% de aumento).

Em relação às encomendas, o "book order" actual é mais do que suficiente para escoar a totalidade dessa produção também. (O delivery é que pode ser mais complicado).

O factor importante é mesmo a resolução dos problemas que existem no TMX e o momento em que inicia a produção efectiva do TMX.

« Última modificação: 2015-11-05 11:16:10 por McKricas »

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #94 em: 2015-11-05 14:11:03 »
Não se trata do inventário embora muitas das unidades tenham que estar aí. Trata-se da Tesla produzir consistentemente muito mais carros do que os que vende, há muitos trimestres.

O valor acumulado dessas diferenças deve andar pelos 9,000 carros produzidos em excesso de entregas.
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #95 em: 2015-11-05 20:19:48 »
Um artigo interessante:

Part 1 : Tesla Motors after 3Q15: Will Optimism Outweigh Losses?
Part 2 : How Tesla Motors’ Revenues Shaped Up in 3Q15
Part 3 : Evaluating Tesla Motors’ Plan to Deliver over 17,000 Cars in 4Q15
Part 4 : How Long Can Tesla Motors’ Sales Grow at Supernormal Rates?
Part 5 : Tesla’s Post-3Q15 Hopes for 30% Gross Margins over Next 18 Months
Part 6 : How Tesla Burned Record Cash in 3Q15—and Why Markets Love it

http://marketrealist.com/2015/11/tesla-motors-3q15-future-optimism-current-losses/

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #96 em: 2015-11-06 11:04:06 »
Tesla Has The Right Approach To Self-Driving Cars
November 5th, 2015 by Mike Barnard

Tesla recently released its Autopilot mode for its cars. It has a fundamentally different intellectual approach to autonomy than Google’s, and it’s superior.

One of my backgrounds is robotics. I spent a year digging my way through PhD theses from robotics programs around the world as I worked on a startup idea for specific applications of swarm-based robots. We got as far as software architecture, simple simulations, 3D modelling of physical robots, and specific applications which had fiscal value. I have some depth here without pretending to be a roboticist, and I’ve continued to pay attention to the field from the outside.

So I feel comfortable in saying that, in general, there are two approaches for robots getting from Point A to Point B.

 - The first is the world map paradigm, in which the robot or a connected system has a complete and detailed map of the world and a route is planned along that in advance accounting for obstacles. Basically, the robot has to think its way past or over every obstacle, which makes for a lot of programming.

 - The second is the subsumption architecture paradigm, in which a robot is first made so that it can survive environments it will find itself in, then equipped with mechanisms to seek goals. The robot then, without any idea of the map of the world, navigates toward Point B. The robot is robust and can stumble its way through obstacles without any thinking at all. The original Roomba vacuum cleaner was a pure subsumption beast.

Obviously, both have strengths and limitations and obviously, at least to me, a combination is the best choice, but it’s worth assessing Tesla’s vs Google’s choices based on this.

Google is starting from the full world map paradigm. For one of its cars to work, it needs an up-to-date centimetre-scale, 3D model of the entirety of the route it will take. Google’s cars are ridiculously non-robust — by design — and when confronted with something unusual will stop completely. Basically, all intelligence has to be provided by people in the lab writing better software.

Why would Google start with this enormous requirement? Well, in my opinion without having spoken to any of the principals in the decision, it’s likely because it fits their biases and blindspots. Google builds massive data sets and solves problems based on that data with intelligent algorithms. They don’t build real-world objects. And the split I highlighted above in world map vs subsumption paradigms is a very real dividing line in academics and research around robotics. It was very easy for Google and world view robotics researchers to find one another and confirm each others’ biases. Others assert that Google is taking a risk-averse approach by leaping straight to Level Four autonomy, and while I’m sure that’s a component of the decision-making process, I suspect it’s a bit of a rationalization for their biases. It’s also being proved wrong by the lack of Tesla crashes to date, but it is early days.

To be clear, Google cars can do things Teslas currently can’t, at least in the controlled prototype conditions that they are testing. They can drive from Point A to Point B in towns and regions that Google has mapped to centimetre scale, which is basically areas south of San Francisco plus a few demo areas. You can’t get in a Tesla, give it an address, and sit back. These are clear performance advantages of the Google model over current Tesla capabilities, and while not trivial, are enabled by the world map model.


Tesla, on the other hand, is starting with the subsumption model. First, the car is immensely capable of surviving on roads: great acceleration, great deceleration, great lateral turning speed and precision, great collision survivability. Then it’s made more capable of surviving. All the car needs to drive on the freeway is knowledge of the lines and the cars around it. Then it adds cameras to give it a hint about appropriate speed. It has only a handful of survivability goals: don’t hit cars in front of you, don’t let other cars hit you, stay in your lane, change lanes when requested, and it’s safe. Because of its great maneuverability — survivability — it can have suboptimal software because it is more able to get out of the way of bad situations. And it has human backup.

And if that’s where Tesla was stopping, everyone who is pooh-poohing its autonomy would be basically correct. But Tesla isn’t stopping there.

Tesla is leveraging intelligent real-world research assistants to put focused, experienced instincts into its cars. They are called the drivers of the Teslas. Every action the Autopilot makes and every intervention a driver makes is uploaded to the Tesla Cloud, where it’s combined with all of the other decisions cars and drivers are making. And every driver passing along a piece of road is automatically granted the knowledge of what the cars and drivers before them have done. In real time.

So, for example, within a couple of days of downloading, Teslas were already automatically slowing for corners that they took at speed before. And not trying to take confusingly marked offramps. And not exceeding the speed limits in places where the signs are obscured.

Within a couple of days of being available, the first people Cannonballed across the USA in under 59 hours with 96% or so of the driving done by the car. Given Google’s requirements, they would have had to send at least two cars out, one or more with a hyper-accurate mapping functionality, then a day or a week later, when the data was integrated, the actual autonomous car. And there would have been no chance of side trips or detours for the Google car. It literally couldn’t drive on a route that wasn’t pre-mapped at centimetre scale. But the Tesla drivers could just go for it.

People are driving Teslas on back roads and city streets with Autopilot, definitely not the optimum location-only situations that others claim Tesla is limited to. And Teslas haven’t hit anything; in fact, have been recorded as avoiding accidents that the driver was unaware of. Survivability remains very high.

Tesla cars are driving themselves autonomously in a whole bunch of places where Google cars can’t and won’t be able to for years or possibly decades. That’s because Teslas don’t depend on perfect centimetre scale maps that are up-to-date in order to do anything. Subsumption wins over world maps in an enormous number of real-world situations.

Finally, Teslas have a world map. It’s called Google Maps. And Tesla is doing more accurate mapping with its sensors for more accurate driving maps. But Teslas don’t require centimetre-scale accuracy in their world map to get around. They are just fine with much coarser-grained maps which are much easier to build, store, manipulate, and layer with intelligence as needed. These simpler maps combined with subsumption will enable Teslas to drive from Point A to Point B easily. They can already drive to the parkade and return by the themselves in controlled environments; the rest is just liability and regulations.

The rapid leaps in capability of the Autopilot in just a few days after release should be giving Google serious pause. By the time its software geniuses get the Google car ready for prime time on a large subset of roads, Teslas will be able to literally drive circles around them.

in http://cleantechnica.com/2015/11/05/tesla-right-approach-self-driving-cars/

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #97 em: 2015-11-06 11:18:41 »
Tesla’s new autopilot system is relying on the cutting edge of machine learning, connectivity and mapping data.

While Tesla’s new hands-free driving is drawing a lot of interest this week, it’s the technology behind-the-scenes of the company’s newly-enabled autopilot service that should be getting more attention.

At an event on Wednesday Tesla’s CEO Elon Musk explained that the company’s new autopilot service is constantly learning and improving thanks to machine learning algorithms, the car’s wireless connection, and detailed mapping and sensor data that Tesla collects.

Tesla’s cars in general have long been using data, and over-the-air software updates, to improve the way they operate.

Machine learning algorithms are the latest in computer science where computers can take a large data set, analyze it and use it to make increasingly accurate predictions. In short, they are learning. Companies like Google , Facebook  and now Tesla are using machine learning as a way to train software to help customers or sell them new services.

Machine learning is the way that computers can become artificially intelligent, and the technology is a form of AI. While Musk has taken a sort of alarmist stance against the dangers of AI, he clarified during the event on Wednesday that he’s only concerned with artificial intelligence that is meant for nefarious purposes.

When a reporter asked Musk during the media Q&A what made his company’s autopilot service different than other computer-based driving assistance features that competing big auto makers are working on, Musk emphasized "learning".

“The whole Tesla fleet operates as a network. When one car learns something, they all learn it. That is beyond what other car companies are doing,” said Musk. When it comes to the autopilot software, Musk explained that each driver using the autopilot system essentially becomes an “expert trainer for how the autopilot should work.”


While most car companies might not be building learning systems, Google’s self-driving cars operate in a similar manner.

In that way, Tesla’s cars are more similar to smart connected gadgets like Nest’s learning thermostat (now owned by Google’s Alphabet), than they are to traditional cars. Nest’s thermostat, using sensors and algorithms, learns its owner’s behavior over time, and through software updates offers increasingly useful services, or even informs Nest’s decisions about its next-generation of hardware.

So, how does Tesla’s autopilot system, and its cars in general, learn? It all starts with data.

Companies building these types of driver-assistance services, as well as full-blown self-driving cars like Google’s, need to teach a computer how to take over key parts (or all) of driving using digital sensor systems instead of a human’s senses. To do that companies generally start out by training algorithms using a large amount of data.

You can think of it how a child learns through constant experiences and replication, explained Nvidia’s Senior Director of Automotive, Danny Shapiro in an interview with Fortune. Nvidia sells high performance chips that enable computers to process large amounts of data, and more recently started selling a computing system, called Drive PX, for self-driving cars and driver-assist applications.

To create a self-driving car, companies feed hundreds of thousands, or even millions, of miles of driving videos and data into a computer’s data model to basically create a massive vocabulary around driving. The algorithms use visual techniques to break down the videos and to understand them. The goal is that when something unexpected happens — a ball rolls into the street — the car can recognize the pattern and react accordingly (slow down because a child could be running into the street after it).

For Nvidia, the company loads this “driving dictionary,” as Shapiro calls it, onto powerful but compact computing hardware that can be used on the car. After that, companies like Google and Tesla add various types of data from different sources to continue to inform the model over time.

Companies try to gather as much data as possible to help a car’s computer make smarter and better decisions on the roads. This includes data from customers driving, data from GPS and maps, and data from company employees driving research cars.

Tesla is making detailed high precision maps to inform its auto pilot system.
The data from Tesla drivers was enabled by the hardware choices that Tesla has made. All Tesla cars built in the past year have 12 sensors on the bottom of the vehicle, a front-facing camera next to the rear-view mirror, and a radar system under the nose. These sensing systems are constantly collecting data to help the autopilot work on the road today, but also to amass data that can make Tesla’s operate better in the future.


Because all of Tesla’s cars have an always-on wireless connection, data from driving and using autopilot is collected, sent to the cloud, and analyzed with software. For autopilot, Tesla takes the data from cars using the new automated steering or lane change system, and uses it to train its algorithms. Tesla then takes these algorithms, tests them out and incorporates them into upcoming software.

Companies will rely on different types of data depending on what they’re trying to do with the cars. For example, Google has used large and expensive LIDAR (light-based radar) sensors on its self-driving cars. But Tesla’s Musk said that LIDAR was basically overkill for what Tesla’s autopilot cars need.

But Musk said that Tesla wanted much more detailed high-precision mapping data for its automated steering and lane change applications than was available through the standard navigation tech. To meet its needs, Tesla has started to build high-precision maps —that have 100 times the level of granularity compared to standard navigation systems — using mostly data from Tesla cars driving on roads, but also some data from Tesla employees driving research cars.

These new services could provide unexpected business models for companies.Musk said that Tesla might be interested in selling the mapping data to other car companies down the road.

Tesla isn’t the only car maker working on driver-assist and self-driving car tech. Google is blazing ahead on its futuristic tech, while Audi has traffic jam assist software. Nvidia’s Shapiro says that most automakers are investigating these technologies.

Nvidia started shipping Drive PX this summer, and Shapiro says that it’s engaged with over 50 companies and researchers. Tesla uses Nvidia chips in the 17-inch screen and the instrument cluster for its Model S and there has been speculation around whether Tesla might use the Drive PX system in future versions of the Model X SUV. Shapiro wouldn’t discuss the specifics of its relationships with Tesla or Audi, which uses Nvidia’s tech in its traffic jam system.

Shapiro cautioned that despite some companies already deploying these technologies, it’s still early days for self-driving car tech. “A huge amount of work will be done on this over the next decade,” he said.

in http://fortune.com/2015/10/16/how-tesla-autopilot-learns/

McKricas

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Re: Tesla (TSLA) - Tópico principal
« Responder #98 em: 2015-11-06 11:25:12 »
A Tesla não é um factor nos carros autónomos. As ajudas ao condutor que a Tesla possuí são as disponibilizadas pela MobilEye, e nem consta que a Tesla possua investigação relevante no domínio de carros autónomos (excepto na imaginação do povo).

Incognitus,

Os dois artigos que coloquei anteriormente pretendem demonstrar que a Tesla "É" um major player nos carros autónomos e que, embora utilize equipamento e sistemas da Mobileye, o Autopilot não se resume a apenas a esse componente, nem esse componente apenas pretende ser o foco principal.

O sistema pretende (e vai) bastante mais além e há um claro objectivo de evoluir o sistema de forma a torná-lo completamente autónomo dentro de poucos anos.
« Última modificação: 2015-11-06 11:25:48 por McKricas »

Incognitus

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Re: Tesla (TSLA) - Tópico principal
« Responder #99 em: 2015-11-06 13:38:04 »
McKricas, o problema destas coisas é que se torna muito fácil de acreditar em coisas absurdas.

Tipo a Tesla tem meia dúzia de tipos a integrar um sistema e diz umas balelas sobre os carros aprenderem, e de repente milhões de pessoas acreditam que a Tesla é um possível líder na área, quando a Google e muitos outros têm milhares de pessoas a trabalhar na área, sensores muito mais avançados, muito mais experiência, dados muito mais densos ... mas nada disso é considerado.

Só posso dizer que presentemente a Tesla NÃO é um factor:
* Em baterias;
* Nem em condução autónoma.

Em ambos os casos os factores são seus fornecedores e vendem o mesmo a quem quiser.

Esses artigos são tanga propagandística que não compreende o que está em questão nem como o Tesla adquire as suas capacidades, nem o que transmite, etc, etc. Nem os sensores do Tesla são suficientes para captar a realidade de forma útil para um carro autónomo, nem naquilo em que poderiam ter algo para transmitir (video, dados do radar) o transmitirão devido aos dados necessários e custo.
"Nem tudo o que pode ser contado conta, e nem tudo o que conta pode ser contado.", Albert Einstein

Incognitus, www.thinkfn.com