The Taycan, Porsche’s answer to the Tesla dominated luxury electric vehicles (EV) market is finally becoming a reality. With over four years of development, the first Taycan cars are expected to be in the hands of customers early in 2020. With a sleek looking exterior and elegant interior, the Porsche Taycan will surely catch the eyes of many EV enthusiasts that are in the market for a luxury electric vehicle. The Taycan Turbo S boasts a range of 450 kilometres, with a 0-100 acceleration of 2.6 seconds. It comes equipped with a 93kWh battery, has 620 horsepower and weighs just over 2,300kg. The car comes in a four-seat configuration with a large touchpad centre console and electronic speed dials. All these specifications sound great on paper, but reading these left me asking two questions; for who is this EV designed for and why are the technical specifications worse than a Tesla Model S? (Burns, 2019)

To attempt to answer the first question, customers who typically buy Porsche cars, buy them as their “second car” after already owning a “utility car”. This is true apart from the Cayenne, Macan and Panamera models which are large enough to function as a utility car. However, the Taycan is smaller than these aforementioned models and larger than Porsche’s other sports cars, leaving it in an awkward “middle-ground”. Would customers buy the Taycan as their utility car or a sports car?

In terms of technical specifications, Tesla’s Model S beats the Taycan in almost every category. It has faster acceleration, more range and horsepower, which is very surprising considering Porsche’s history of making very fast, high-quality cars. In my opinion, Porsche missed the mark here in conceding to Tesla on specifications. Similar to the 918 Spyder, which is the fastest stock car in production, the Taycan could have been faster than the Tesla, which could have made a  statement in the EV market. No one willing to spend $185,000 wants to be in the second-fastest car on the road. (Templeton, 2019)

References

Burns, M. (2019). Porsche Taycan vs Tesla Model S: Spec for spec, price for price – TechCrunch. [online] TechCrunch. Available at: https://techcrunch.com/2019/09/04/porsche-taycan-vs-tesla-model-s-spec-for-spec-price-for-price/ [Accessed 2 Oct. 2019].

Templeton, B. (2019). New $104K Porsche Taycan Looks Nice But Is No ‘Tesla Killer’. [online] Forbes.com. Available at: https://www.forbes.com/sites/bradtempleton/2019/10/14/new-104k-porsche-taycan-looks-nice-but-is-no-tesla-killer/#37a52fe71454 [Accessed 2 Oct. 2019].

Over the past year, deepfakes have become so good at manipulating images, video and audio that they may soon become indistinguishable from reality. If this were to occur, the societal implications would be substantial. This is especially worrying with the recent rise of fake news outlets that have successfully managed to influence political discourse during national elections. Deepfakes could take fake news to the next level by actually supplying readers with a depiction of “proof” that would further cause a polarisation of society based on political views.

Keeping this in mind, it is important that we can find a way to counter deepfakes and expose manipulated images, video and audio to keep believing in what we see online. This blog post will explore three possible ideas on how deepfakes could be countered and exposed.

1. We could trust in trained individuals to make value judgements about potential deepfake content. Sarah T. Roberts, an information scholar at UCLA suggests that these people could be trained in spotting for signs of manipulation and taking down questionable content from online platforms, helping to make a safer and more trustworthy internet.
2. Stricter legal punishments on image, video and audio forgery could discourage some deepfake artists from creating them. This could potentially reduce the number of deepfakes that are created and distributed online.
3. Developing machine learning algorithms for the purpose of analysing uploaded media and online platform content can help filter out suspicious content. According to John Villasenor, an engineering professor, deepfake videos may seem indistinguishable from real videos to the human eye, but contain very slight errors that only machines would be able to pick up on. If these algorithms could be perfected to the point that they can reliably be scaled out to online platforms, it would contribute to a more trustworthy internet.

Sources:

https://www.cnbc.com/2019/10/14/what-is-deepfake-and-how-it-might-be-dangerous.html

https://www.theverge.com/2019/6/10/18659432/deepfake-ai-fakes-tech-edit-video-by-typing-new-words

https://www.technologyreview.com/s/614343/the-worlds-top-deepfake-artist-wow-this-is-developing-more-rapidly-than-i-thought/