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The CEO said when asked about Tesla achieving its promised unsupervised self-driving on HW3 vehicles:
We are not 100% sure. HW4 has several times the capability of HW3. It’s easier to get things to work on HW4 and it takes a lot of efforts to squeeze that into HW3. There is some chance that HW3 does not achieve the safety level that allows for unsupervised FSD.
Linus Torvalds, the creator and maintainer of the Linux kernel, talks modern developments.
https://peterszasz.com/engineering-managers-guide-to-effective-annual-feedback
The main goals of a regular, written feedback cycle are:
These promote:
Listen to the podcast in the post
“I just created a AI-Generated podcast by feeding an article I write into Google’s NotebookLM. If I hadn’t make it myself, I would have been 100% fooled into thinking it was real people talking.”
In the next couple of decades, we will be able to do things that would have seemed like magic to our grandparents.
This phenomenon is not new, but it will be newly accelerated. People have become dramatically more capable over time; we can already accomplish things now that our predecessors would have believed to be impossible.
We are more capable not because of genetic change, but because we benefit from the infrastructure of society being way smarter and more capable than any one of us; in an important sense, society itself is a form of advanced intelligence. Our grandparents – and the generations that came before them – built and achieved great things. They contributed to the scaffolding of human progress that we all benefit from. AI will give people tools to solve hard problems and help us add new struts to that scaffolding that we couldn’t have figured out on our own. The story of progress will continue, and our children will be able to do things we can’t.
In software development, “technical debt” is a term used to describe the accumulation of shortcuts, suboptimal solutions, and outdated code that occur as developers rush to meet deadlines or prioritize immediate goals over long-term maintainability. While this concept initially seems abstract, its consequences are concrete and can significantly affect the security, usability, and stability of software systems.
Technical debt arises when software engineers choose a less-than-ideal implementation in the interest of saving time or reducing upfront effort. Much like financial debt, these decisions come with an interest rate: over time, the cost of maintaining and updating the system increases, and more effort is required to fix problems that stem from earlier choices. In extreme cases, technical debt can slow development to a crawl, causing future updates or improvements to become far more difficult than they would have been with cleaner, more scalable code.
One of the most significant threats posed by technical debt is the vulnerability it creates in terms of software security. Outdated code often lacks the latest security patches or is built on legacy systems that are no longer supported. Attackers can exploit these weaknesses, leading to data breaches, ransomware, or other forms of cybercrime. Furthermore, as systems grow more complex and the debt compounds, identifying and fixing vulnerabilities becomes increasingly challenging. Failing to address technical debt leaves an organization exposed to security risks that may only become apparent after a costly incident.
Technical debt also affects the user experience. Systems burdened by outdated code often become clunky and slow, leading to poor usability. Engineers may find themselves continuously patching minor issues rather than implementing larger, user-centric improvements. Over time, this results in a product that feels antiquated, is difficult to use, or lacks modern functionality. In a competitive market, poor usability can alienate users, causing a loss of confidence and driving them to alternative products or services.
Stability is another critical area impacted by technical debt. As developers add features or make updates to systems weighed down by previous quick fixes, they run the risk of introducing bugs or causing system crashes. The tangled, fragile nature of code laden with technical debt makes troubleshooting difficult and increases the likelihood of cascading failures. Over time, instability in the software can erode both the trust of users and the efficiency of the development team, as more resources are dedicated to resolving recurring issues rather than innovating or expanding the system’s capabilities.
While technical debt can provide short-term gains by speeding up initial development, the long-term costs are much higher. Unaddressed technical debt can lead to project delays, escalating maintenance costs, and an ever-widening gap between current code and modern best practices. The more technical debt accumulates, the harder and more expensive it becomes to address. For many companies, failing to pay down this debt eventually results in a critical juncture: either invest heavily in refactoring the codebase or face an expensive overhaul to rebuild from the ground up.
Technical debt is an unavoidable aspect of software development, but understanding its perils is essential for minimizing its impact on security, usability, and stability. By actively managing technical debt—whether through regular refactoring, code audits, or simply prioritizing long-term quality over short-term expedience—organizations can avoid the most dangerous consequences and ensure their software remains robust and reliable in an ever-changing technological landscape.
https://www.bbc.com/future/article/20240912-what-riddles-teach-us-about-the-human-mind
“As human beings, it’s very easy for us to have common sense, and apply it at the right time and adapt it to new problems,” says Ilievski, who describes his branch of computer science as “common sense AI”. But right now, AI has a “general lack of grounding in the world”, which makes that kind of basic, flexible reasoning a struggle.
AI excels at pattern recognition, “but it tends to be worse than humans at questions that require more abstract thinking”, says Xaq Pitkow, an associate professor at Carnegie Mellon University in the US, who studies the intersection of AI and neuroscience. In many cases, though, it depends on the problem.
A bizarre truth about AI is we have no idea how it works. The same is true about the brain.
That’s why the best systems may come from a combination of AI and human work; we can play to the machine’s strengths, Ilievski says.
At the age of 94, this is what the great Clint Eastwood looks like.
Standing, lucid, brilliant, directing his latest film. Eastwood himself says it: “I don’t let the old man in. I keep myself busy. You have to stay active, alive, happy, strong, capable. I don’t let in the old critic, hostile, envious, gossiping, full of rage and complaints, of lack of courage, which denies to itself that old age can be creative, decisive, full of light and projection. Getting older is not for sissies.”
~Clint Eastwood
https://peterszasz.com/how-to-lead-your-team-when-the-house-is-on-fire/
For years, tech firms were fighting a war for talent. Now they are waging war on talent.
This shift has led to a weakening of the social contract between employees and employers, with culture and employee values being sidelined in favor of financial discipline and free cash flow.
The operating environment has changed from a high tolerance for failure (where cheap capital and willing spenders accepted slipped dates and feature lag) to a very low – if not zero – tolerance for failure (fiscal discipline is in vogue again).
While preventing and containing mistakes staves off shocks to the income statement, it doesn’t fundamentally reduce costs. Years of payroll bloat – aggressive hiring, aggressive comp packages to attract and retain people – make labor the biggest cost in tech.
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Of course, companies can reduce their labor force through natural attrition. Other labor policy changes – return to office mandates, contraction of fringe benefits, reduction of job promotions, suspension of bonuses and comp freezes – encourage more people to exit voluntarily. It’s cheaper to let somebody self-select out than it is to lay them off.
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Employees recruited in more recent years from outside the ranks of tech were given the expectation that we’ll teach you what you need to know, we want you to join because we value what you bring to the table. That is no longer applicable. Runway for individual growth is very short in zero-tolerance-for-failure operating conditions. Job preservation, at least in the short term for this cohort, comes from completing corporate training and acquiring professional certifications. Training through community or experience is not in the cards.
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The ability to perform competently in multiple roles, the extra-curriculars, the self-directed enrichment, the ex-company leadership – all these things make no matter. The calculus is what you got paid versus how you performed on objective criteria relative to your cohort. Nothing more.
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Here is where the change in the social contract is perhaps the most blatant. In the “destination employer” years, the employee invested in the community and its values, and the employer rewarded the loyalty of its employees through things like runway for growth (stretch roles and sponsored work innovation) and tolerance for error (valuing demonstrable learning over perfection in execution). No longer.
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http://www.rosspettit.com/2024/08/for-years-tech-was-fighting-war-for.html
The Curse of Knowledge is a cognitive bias that occurs when someone incorrectly assumes that others have the same or enough background to understand each other.
You can avoid the negative effects of the curse of knowledge by constantly questioning your assumptions as to how much exactly your audience knows.
How a manually misconfigured and untested server continued running old test code during a live trading session, lead the bot to make $8.65 billion in unintended stock trades in just 28 minutes.
https://benmeer.com/newsletter/staying-calm/
Stress is your body’s way of signaling that something important is happening.
https://www.demandcurve.com/newsletters/growth-newsletter-199
Look at the “benefit of a benefit.”
Step 1:
Write a list of your product’s benefits AND its downsides.
Step 2:
Analyze each and ask, “what’s a unexpected / obvious / helpful / interesting / funny / convenient / comforting / amazing / wild / beautiful / exciting / weird… benefit of this benefit/downside?”
In other words, what’s a second-order benefit of that benefit/downside?
It can either be directly for the user (kids on a trampoline) or for the real buyer/user (relaxed parent).
https://www.elysian.press/p/employee-ownership
The article advocates for employee ownership of companies, using Central States Manufacturing as a model. The company, owned by its employees through an Employee Stock Ownership Plan (ESOP), demonstrates how such structures can create significant wealth for workers across all levels, improve long-term company performance, and reduce wealth inequality. Employee ownership aligns worker and company interests, leading to sustainable growth and better employee benefits. The article highlights the benefits of ESOPs and calls for broader adoption and awareness of such models.
https://www.chrbutler.com/understanding-the-eye-mind-connection
The intricate relationship between the eyes and the brain, often termed the eye-mind connection, reveals that vision is predominantly a cognitive process. This understanding has profound implications for fields such as design, where capturing and maintaining attention is paramount. This essay delves into the nuances of visual perception, the brain’s role in interpreting visual data, and how this knowledge can be applied to effective design strategies.
This cognitive aspect of vision is evident in phenomena such as optical illusions, where the brain interprets visual information in a way that contradicts physical reality. These illusions underscore that what we “see” is not merely a direct recording of the external world but a constructed experience shaped by cognitive processes.
Understanding the cognitive nature of vision is crucial for effective design. Designers must consider how the brain processes visual information to create compelling and engaging visuals. This involves several key principles: