Autonomous driving continues to have a torrid time as its devotees adjust to the reality that has been obvious for quite some time.
Argo AI is the latest victim which – combined with Tesla being the subject of 2 NHTSA defect investigations and plummeting valuations – puts autonomous driving firmly in the capitulation phase of the investment bubble cycle.
Argo AI has been in trouble for some months, having announced layoffs four months ago. But now it appears that its backers have declined to throw good money after bad, leaving it insolvent. With no one else showing up, the only option remaining is to close its doors.
And thus is another headstone added to the increasingly well-populated graveyard.
What happened to Argo?
The problem is simple.
Targets for autonomous driving were set by executives who knew nothing about AI and assumed that the problems would soon be solved. Consequently, they thought they would have revenues by now and set their budgets accordingly.
For example, when Ford and VW invested in Argo AI, they set expectations for vehicles to be on the road by 2021. Now that revenues may not show up for another six years or more, they face raising money in one of the most challenging investment climates we have seen in 14 years.
This is why autonomous driving companies are dropping like flies, and I suspect that there are more to come.
Deep learning isn’t street-ready
The predominant method by which an autonomous driving system perceives its surroundings is deep learning. In reality, this is nothing more than a sophisticated statistical pattern recognition system. This means that deep learning has no causal understanding of what it is doing – and as such, is unable to think outside of the box.
The net result is that whenever a situation arises that the machine has not been explicitly taught, it will fail to correctly interpret the situation, which will cause the vehicle to make a mistake. The problem is that this occurs all the time on the open road. This is why the speed of progress has been far slower than many had hoped.
Furthermore, this slowness has allowed the laggards to catch up. This supports my long-held view that when shopping for an autonomous driving solution, OEMs will have plenty of equally good offerings to choose from.
This seems to have finally dawned on Ford and VW where Ford took a $2.7 billion write down (Q3 2022) on its investment in Argo AI, and switched its priority to ADAS (Level 2+ and 3) rather than Level 4 and 5.
Hard road ahead for autonomous driving
Consequently, I see no reason to change RFM’s original target (set in 2017) for autonomous driving technology reaching commercialisation in 2028.
With the way things are going, this is increasingly looking like it may be optimistic. But six years is a long time in the technology industry. So I think that 2028 is still achievable.
I remain optimistic about this technology in the long term. But the road forward is only going to get harder.
Where are AVs on the Gartner hype cycle I wonder?