Apple’s rumored $1,000 tabletop robot could launch in 2027 with a swiveling display and Siri AI, but software delays may push its release into 2028.
The post Apple’s $1,000 Tabletop Robot Could Arrive in 2027 appeared first on TechRepublic.
I am an alfista. The word is Italian for someone devoted to the cars produced by Alfa Romeo. Together with the thousands of others who share that devotion, I am one of the alfisti. Nobody chooses to join the ranks of the alfisti on the numbers alone. We love the brand for reasons that have little to do with logic, and we choose these beautiful, difficult, idiosyncratic cars because of how they make us feel.
October was an exciting month to be an alfista. Alfa Romeo brought a new concept car to the Paris Motor Show, a vehicle it named Cuorerosso—red heart. In fact, it was a good month for car enthusiasts of every stripe. In the same week that Alfa showed the Cuorerosso in Paris, Porsche introduced its Mission S concept in New York, and Tesla finally unveiled the Roadster it had been promising for years. These three cars, each unique in their own way, share something important in common: each was built for a world in which the act of driving can be, and increasingly is, handed over to software.
All three cars are worth examining in their own right, as moments in the history of the automobile and in the history of business. But what makes them worth looking at together is that each gives a different answer to the same question—what is a car for once a machine can drive it? That question is the automotive version of one that leaders in every industry are facing right now. Once machines can do the work, what are people for?
Tesla makes the machine the star
The Tesla Roadster comes in four versions. The most eye-catching of them, the Rocket, uses compressed-air thrusters to lift the car off the ground and set it down again. Tesla estimates that its vehicle can reach 60 mph in 0.59 seconds. The faster versions produce a megawatt of power, and the company claims they can hit 230 mph, with downforce fans pulling them onto the road. Steering and braking are handled entirely by wire, through software, with no direct mechanical link.
Few companies would build a flying car simply to show that they can, and while I have no desire to drive one, I admire the ambition. Top Gear summed up precisely how I feel about the new Tesla when it described the Roadster’s abilities as mostly useless and completely captivating.
That verdict should not be read as a criticism. What Tesla is selling is spectacle. The car performs and the human watches, a relationship that fits perfectly with the priorities of a company whose bigger bet is on cars that drive themselves. In the world Tesla is building, the machine is the star, and the human is simply the audience.
Porsche puts the needle back
The same week, Porsche showed the Mission S in New York, a mid-engined concept for a new supercar line above the 911. For the venue, it chose the Queens pier where it had presented the 550 Spyder in 1953.
The pier was a gesture toward the past, and Porsche is clearly looking in the same direction for its future. There is no center screen and no passenger screen inside the car. Instead, your phone clips in and becomes the display. The driver faces five round gauges, and the tachometer has a real, physical needle.
This is not nostalgia. Porsche is under financial pressure, and CEO Michael Leiters is answering it with a bet on identity: a Porsche, he says, must be recognizable as a Porsche at first glance. A German engineering company with a reputation for performance has decided to compete instead on character. It has taken the screens out and put something mechanical back in. This is a design choice, but it is also a business decision, and I think a smart one.
Alfa Romeo names a car after the heart
The Cuorerosso that Alfa unveiled in Paris on October 12 is a 4.7-meter, four-seat coupe finished in a red that darkens almost to black as the light changes. One proposed setup pairs Alfa’s 2.9-liter V6 with a full hybrid system and all-wheel drive. The company presents the car as a manifesto rather than a preview of a production model.
The manifesto’s governing principle is Bellezza Necessaria—necessary beauty—which means keeping only what serves the driver. One instrument mode, Concentrato, shows drivers less information the more engaged they become. Where most technology competes for our attention, this mode hands it back to the road.
The Cuorerosso also uses steer-by-wire, the same technology Tesla has put in the Roadster, but here it serves a different purpose. Santo Ficili, CEO of Alfa Romeo and Maserati, put it plainly: “Technology, function and quality are always at the service of emotions and driving pleasure.”
Alfa has had its difficulties, as every alfista knows. But the brand has never been confused about why it exists. That is why it named this car after the heart.
What survives automation
AI is making capability abundant. A song, a video, an app, or a business plan can now be produced in a fraction of the time that it used to take. The engineering behind physical products is heading in the same direction. As the cost of turning ideas into products is slashed, the benefits that come with being the first to market with some new capability fall. The result is that capability can no longer, in most cases, be an enduring differentiator.
Tesla’s Roadster can reach 60 mph in 0.59 seconds, according to the company’s estimates. Someone will beat that, and when they do, the number will go from being the thing that defines the Roadster to just another line in a comparison table. The thrusters will lose their novelty the day a second company builds a car that leaves the ground. Once a capability is available to everyone, it stops saying anything about the company that has it.
What increasingly defines a company, instead, is its taste and the emotional pull that its taste creates. Taste is knowing what belongs and what does not. The three cars unveiled in October are three different answers to what belongs in an automobile. Tesla’s offering caters to those with a taste for spectacle, Porsche’s to those who look for character, and Alfa’s to those who look for feeling.
These three answers are arriving at a moment when the act of driving is itself becoming optional. It is natural to assume that once AI can drive the car and not just help design it, taste will matter less than ever. The thinking is that a world in which AI does the work is a world that runs on efficiency, and efficiency leaves no room for taste. The history of transportation suggests the opposite. The car made the horse unnecessary, but horses did not vanish. They became a passion. Nobody rides a horse today because it is the most efficient way to get somewhere. They ride because the act of riding matters to them. When a technology makes an activity unnecessary, the activity survives only as something people choose, and people choose with the heart. AI is doing this to driving, and it is about to do it to a great deal else.
What this means for leaders
Most of us do not run car companies, but the question that Tesla, Porsche, and Alfa have each answered in their own way is one that every leader now has to answer too: Once your capabilities can be matched, what makes people choose you?
• Do not compete on capability alone. Whatever AI helps you do today, it will help your competitors do before long. Capability earns attention, and attention is worth having, but it is not what makes anyone stay.
• Know what your taste is and who shares it. Tesla’s loyalists want spectacle, Porsche’s want character, Alfa’s want feeling. Each company knows exactly which it is offering. If you cannot say what belongs in your product and what does not, neither can your customers.
• Invest in judgment. AI can give you a hundred options at almost zero cost. What it cannot give you is the person who knows which of those belongs and which 99 you should throw away. That kind of judgment—itself a form of taste—is developed over years, and no model can generate it. Hire for it. Reward the people who say no and protect the people who decide what sits at the emotional core of your brand.
What we choose when we no longer have to
If the day comes when I no longer need to drive, I know I will still want to take my old Alfa Romeo out for a spin. It nourishes something in my heart and in my soul. It speaks to me in a way that goes far beyond the question of simple utility. It is precisely what I would choose to do with the increased freedom that comes when necessities are taken care of. As AI automates more and more of the realm of necessity, we will have to think harder about what is worth doing with the freedom we gain. Businesses will have to think harder, too, about what people want from that freedom and what they can offer that makes it worth having.
The number of women working for the Trump administration, specifically in top national security roles, keeps falling.
That finding comes from a new report by Democrats on the Senate Foreign Relations Committee. The Oct. 30 report, titled “Tru…
The debate about AI and work often focuses on the jobs that will disappear, which tasks will be automated, and which skills and qualities will be valued in the future. It is more seldom that I read articles that analyze the impact of AI on exhaustion and pleasure at work. And those questions are usually asked about “workers” in general, as if the answers were the same for men and women. There are many reasons why they are not. Because women and men are concentrated in different occupations, perform different tasks within the same organizations, and are judged differently for the same work, AI affects women’s work in very specific ways.
Is the overall effect positive or negative? It isn’t easy to say, so I made an old-fashioned list of pros and cons, the kind people draw up when deciding whether to change jobs or leave a relationship. I ended up with more negatives than positives: five reasons to be hopeful and eight reasons to worry.
On the hopeful side
#1. Today’s job growth is happening mostly in women’s jobs, and they aren’t very much exposed to AI. In 2025, health care and social assistance accounted for almost all net job creation in the US, about 405,000 jobs in health care and 308,000 in social assistance. If it weren’t for those two sectors, the US would have lost jobs last year. The BLS anticipates that this will continue to be the case in the coming decade, because of population ageing. We will need a lot of caregivers in the future, and LLMs can’t take their place. That protects women’s employment, but it does little for their pay: care work remains badly paid, and in the US its growth also depends on public money that hinges on political choices. The coming midterms will say a lot about where things are heading.
#2. AI could make “greedy jobs” less hostile to women. A big part of the pay gap is attributable to the unequal distribution of the highest-paying jobs. The so-called “greedy jobs” reward presenteeism and excessive workloads, which penalizes everyone who can’t give work all of their time. In law, finance, consulting or medicine, value is tied to being the one person who knows the client or the case. If AI makes expertise portable, making a client’s or a case’s history immediately accessible to other colleagues, then it could reduce the premium on being irreplaceable. This is what digital records did to pharmacy, which went from a male-dominated, unequal profession in the 1970s to an equal one in the US. Of course, we’ll still need employers to decide to redesign those jobs, and that can never be guaranteed.
#3. Hurrah, some of the most tedious office chores are now being automated. Writing meeting minutes, taking notes, organising schedules, drafting follow-up emails: most of these “non-promotable tasks” are important but do nothing to advance the career of those who do them. And they fall predominantly on women’s shoulders (it shouldn’t come as a surprise: they’re exactly like household chores). The time spent on them could be spent on more visible tasks that can earn you a promotion. So AI tools that automate them are more than welcome! Likewise, there’s less paperwork in care jobs. Nurses and doctors are worn down by paperwork. Using AI tools can help them focus more on patients, which happens to be the part of the job they like best.
#4. The barriers to entrepreneurship and to building with tech are lower now. Women who start companies have always had to do more with less. In the US, startups founded only by women still get roughly 2% of venture capital (and this share isn’t budging). AI makes it possible to start small and still go far. On your own, you can accomplish so much more with an army of “agents”! You can create a website with very little money, draft contracts, answer customers… According to Carta, the share of new startups with a single founder rose from about 24% in 2019 to 36% in the first half of 2025. AI-assisted coding also enables people to develop digital tools without knowing how to code, which is remarkable in a field where women are in the minority.
#5. Relational skills are gaining value. As AI takes over the codifiable part of cognitive work, the value of what it doesn’t do so well could go up: coordinating, caring, exercising judgment in context. A lot of women have acquired these skills through decades of being expected to look after others and manage their emotions. If AI does raise the value of those skills, the market may have to pay more for them and stop seeing them as “naturally” feminine and therefore of little value.
On the worrisome side
#1. The most exposed white-collar jobs are disproportionately held by women. In rich countries, according to the International Labour Organization, 9.6% of women’s jobs fall into the highest category of exposure to generative AI, compared with 3.5% of men’s jobs. The reason is that women are concentrated in clerical jobs: assistants, secretaries, payroll and data entry clerks. Not all these jobs will disappear. But we already have an idea of how they can change. Translation is a mostly female profession (around seven in ten translators and interpreters in the US are women). A big share of translators have lost work to generative AI (and others have changed professions already). Many of those who still have work now spend their days editing machine output, for less money.
#2. The first rungs of the ladder are disappearing. For generations, junior administrative and clerical jobs were a route into employment, and upward mobility, for women without higher education. A secretary could become an office manager, then an executive assistant, then an operations manager. If AI eliminates most of these entry points, the career ladder gets cut at the bottom, and that’s bad news for women.
#3. Women who use AI pay a competence penalty. In a study of more than 1,000 engineers reported by Harvard Business Review, identical code was judged differently depending on who was known to have written it. Women who used AI saw their perceived competence drop by 13%, compared with 6% for men, and by 26% when the reviewers were men who did not use AI themselves. This is a digital version of the Matilda effect: when a woman uses the machine, the credit goes to the machine; when a man uses it, his judgment in choosing to use it is valued. Women are caught in a double bind: they are judged less competent if they use AI and less up to date if they don’t.
#4. Women are largely absent from one of today’s most lucrative industries. AI is already one of the best-paid segments of the market. According to LinkedIn, women accounted for only 26% of AI hires in 2025, compared with half of all hires in other sectors, and they hold only 13% of C-suite roles at AI companies.
#5. The tools are built mostly by men, and it shows. LLMs learn from data that reflects a world where men have long held the best jobs and earned the highest salaries. German researchers at the Technical University of Würzburg-Schweinfurt asked chatbots for salary negotiation advice using profiles that were identical except for gender. Women were told to aim lower. In one case, the model suggested $280,000 for a woman and $400,000 for a man. Years earlier, Amazon had to drop an experimental recruiting tool after discovering it penalised CVs containing the word “women”, as in “women’s chess club captain.” The system had been trained on ten years of applications, most of them from men. In hiring, evaluation and career advice, the same biases get repeated at scale.
#6. New office chores replace the old ones. Someone still has to read the automated minutes, improve the AI-generated drafts and catch the made-up figures and other hallucinations before they go out. AI slop takes time to process. I suspect a lot of this “cleanup” lands where office chores have always landed. If that’s right, some of the time saved by automating the old chores gets eaten by the new ones.
#7. The jobs AI can’t do are the ones it watches most closely. Call centers and home care are good examples. In the US, 85% of home care workers are women, and since 2020 those paid through Medicaid have had to log every visit in an app that tracks them by GPS and checks their identity. Call centre and retail workers know the same timed tasks and automated schedules. These women keep their jobs, but they lose more and more control over how they do them.
#8. Deepfakes make visibility more dangerous for women. Nearly all deepfake videos online are pornographic, and 99% of the people targeted in them are women. Public life makes it worse: in the US Congress, women were 70 times more likely than men to be targeted. Journalists, politicians, founders, anyone whose career depends on being seen now faces a risk men rarely do. Many women are likely to respond by stepping back (and who could blame them?) After facing online abuse, 38% of women journalists surveyed by UNESCO said they had lowered their public profile.
On balance
My list clearly has more negatives than positives, which in itself doesn’t mean much. Counting items doesn’t tell you how much each one weighs. Besides, the list is far from comprehensive. You may have other arguments on the credit or the debit side…
Still, having drawn up both columns, I would say the balance is negative for women’s work, at least for now. The main reason is a difference in timing. Most of the negatives are already happening: women hold the most exposed jobs, the first rungs of the career ladder are disappearing, women who use AI are judged more harshly, they are a small minority in the sector where the money is, the tools carry biases, the jobs AI can’t do are increasingly monitored, and deepfakes make public visibility riskier. Most of the positives, on the other hand, depend on conditions that haven’t yet been met: greedy jobs will only loosen if firms deliberately redesign work, the time freed from office chores and paperwork can easily be swallowed by new tasks, relational skills will only pay if employers finally choose to recognise them…
The balance could still shift, of course. What happens next will depend on choices made inside companies, about job design, evaluation and hiring in AI, and on choices made at the ballot box, about how much public money goes to care.
Oculus VR and Anduril cofounder Palmer Luckey, worth $5.9 billion, opposes the proposed tax hike but is opting to stay: “California is something special.”
While millions of Americans struggle to make ends meet, some U.S. Senate candidates like Mark Warner and Pete Ricketts are worth as much as $200 million.
Waymo and Toyota plan to test self-driving bZ4X robotaxis in Japan in 2027, with factory-integrated technology supporting future international expansion.
The post Waymo and Toyota to Test Self-Driving SUVs in Japan in 2027 appeared first on TechRepublic.
The law firm’s dissolution raises broader questions about the sustainability of business models heavily dependent on high-profile individuals.
Hello and welcome to Modern CEO! I’m Stephanie Mehta, CEO and chief content officer of Mansueto Ventures. Each week this newsletter explores inclusive approaches to leadership drawn from conversations with executives and entrepreneurs, and from the pa…
I don’t consciously think about my first job when I meet with leaders in the electronics industry to talk about trade policy. But my young days in an Illinois cornfield will always shape how I view, and do, work.
My hometown in western Illinois had…
