There are many reasons robotics companies fail. From an ill-conceived idea to poor execution or the inability to raise funding, building and running a sustainable robotics company is challenging. This is never a fun recap to write. We don't want to see startups fail, but inevitably many do. The last couple of years have been especially difficult thanks to a global pandemic, economic uncertainties and ongoing supply chain issues.

The layoffs are part of a restructuring that iRobot said will save the company up to $10 million in 2022 and between $30-$40 million in 2023. This was the same day iRobot announced it was being acquired by Amazon for $1.7 billion. However, iRobot said the two events are not related. To better align costs with near-term revenue, part of the restructuring includes shifting certain non-core engineering functions to lower-cost regions and increasing use of iRobot's joint design manufacturing (JDM) partners. "These actions help support the company's near-term priorities to drive innovation by executing on its product roadmaps, optimize inventory levels across all major channels, expand DTC sales and position the business for profitable growth in 2023," iRobot said in its earnings statement.

Human intuition is the hardest problem for self-driving cars.

Autonomous cars are being programmed to interpret road traffic and pedestrians in order to drive more like humans. A key issue with driverless cars has been their ability to interpret traffic and other upcoming object such as pedestrians, where they become overly cautious. For example, if a person appears as if they will cross the street but then changes their mind, a driverless vehicle may stop and wait. Engineers at Perceptive Automata - based near Boston - has teamed up with Hyundai Cradle, the car firm's technology investment arm, to create software that anticipates what pedestrians, cyclists and other motorists might do. The newly-developed artificial software will then help the driverless vehicles predicate what is coming up more like a human.

Hyundai wants to teach its autonomous cars to think like humans, investing in AI specialists Perceptive Automata to develop new software for self-driving vehicles that will mean your car is as good at spotting unpredictable hazards as you are. Hyundai's Cradle divison - a department set aside for innovation, not unlike BMW's i division - made the decision to partner with the American startup after Perceptive Automata developed new software that is able to predict the often unpredictable intentions of pedestrians, cyclists and other road users. "One of the biggest hurdles facing autonomous vehicles is the inability to interpret the critical visual cues about human behaviour that human drivers can effortlessly process," says Hyundai Cradle vice-president, John Suh. "Perceptive Automata is giving the AV industry the tools to deploy autonomous vehicles that understand more like humans, creating a safer and smoother driving experience." Considered one of the stumbling blocks to our autonomous future, the erratic behaviour of human road users is much harder to predict than that of other self-driving cars. The latter, it is presumed, would be talking to each other, but humans remain the unpredictable off-line element.

Driving in a busy city, you have to get good at scrutinizing the body language of pedestrians. Your foot hovers somewhere between the gas and the brake, waiting for your brain to triangulate their intent: Is that one trying to cross the street, or just waiting for the bus? Still, a whole lot of the time you hit the brakes for nothing, ending up in a kind of dance with the pedestrian (you go, no you go, no YOU go). If you think that's frustrating, then you've never been a self-driving car. As human drivers slowly go extinct (and human pedestrians don't), autonomous vehicles will have to get better at decoding those unspoken intersection interactions.