haruki zaemon

A quantum computer in the next decade could crack the encryption our society relies on using Shor’s Algorithm.

One of the things that many facilitators and hosts worry about with complex facilitation practices is the outcomes and the quality of the experience. It is the hardest thing to let go of and probably the last piece of “performative facilitation” that deeply experienced facilitators are able to release.

But that desire and drive for a particular emotional outcome can be as damaging to a meeting as a drive toward a particular material outcome.

Don’t tell people what they will experience. Don’t pre-determine their outcomes or their emotional journey on the day. Let go of that control and enable the environment.

the models tended to produce images of people that look white and male, especially when asked to depict people in positions of authority.

the models’ output overwhelmingly reflected stereotypical gender biases. Adding adjectives such as “compassionate,” “emotional,” or “sensitive” to a prompt describing a profession will more often make the AI model generate a woman instead of a man. In contrast, specifying the adjectives “stubborn,” “intellectual,” or “unreasonable” will in most cases lead to images of men.

In almost all of the representations of Native Americans, they were wearing traditional headdresses, which obviously isn’t the case in real life.

image-making AI systems tend to depict white nonbinary people as almost identical to each other but produce more variations in the way they depict nonbinary people of other ethnicities.

If you write more for internal consumption, consider how to write for two readers: the change for your ideal readers, and assurance for your secondary readers. You might have to change your ideal reader in the middle, but that’s practice. Start with the ideal reader, then add what’s needed for the secondary reader.

The Worry Police aren’t curious; they are concerned.

I frequently have front-row seats for their theatre. I am frequently accountable for unpacking their machinations and translating them into action while simultaneously cleaning up their wake of fear and confusion.

Leaders have real power because they understand how to build trust. They build their judgment with the people who understand the problem and have defensible opinions.

Leaders take the time to understand the situation entirely; they communicate clearly and consistently to their audience.

Leaders are intensely curious. This curiosity creates shared understanding and long-term purpose.

Designers often feel frustrated by seemingly off-topic or untimely feedback when presenting to other functions (product, engineering, marketing, etc).

It can also be hard to handle criticism in cross-functional presentations, especially after spending tons of energy.

Critiques force designers to set up the conversation so the scope of feedback is valuable to them at a given point in time, but in a safer space than an evaluative presentation.

Critiques can help designers foresee objections, strengthening their designs, and develop the ability to handle them with grace.

People find it difficult to give up control when they see their role and status as tightly linked to their decision-making authority and delegating responsibility as a diminution of their power.

Clarify decision roles, rights, and accountability. Write down the decisions you’re responsible for, individually and collectively—delegation shouldn’t be confused with dereliction of duties.

Coach people, encourage them to assimilate information, and to reflect on decisions, especially when the outcomes were not as intended.

Open up the decision-making process, invite people into critical meetings as an opportunity to observe and contribute their insights.

Structure meetings around decisions, encourage participants to share different perspectives and challenge each other, summarise the decisions and specify the people accountable for implementing them.

Communicate high-profile, critical decisions so that people can learn about how judgements were made. The scrutiny that comes from this transparency might even improve the quality of decision-making, too.

They had to see all the WIP, but then they made much better decisions.

Caused by the bacterium Yersinia pestis, plague is not a thing of the past. Every year, cases are reported in Africa, some parts of Asia, South America, and the U.S. Known for killing millions in the Middle Ages, people get infected with the plague after coming into contact with a rodent flea or being bitten by one infected with the plague.

At every step and every level there’s an abundance of detail with material consequences. Surprising detail is a near universal property of getting up close and personal with reality. The more difficult your mission, the more details there will be that are critical to understand for success.

Before you’ve noticed important details they are, of course, basically invisible. It’s hard to put your attention on them because you don’t even know what you’re looking for. But after you see them they quickly become so integrated into your intuitive models of the world that they become essentially transparent.

This means it’s really easy to get stuck. Stuck in your current way of seeing and thinking about things. Frames are made out of the details that seem important to you. The important details you haven’t noticed are invisible to you, and the details you have noticed seem completely obvious and you see right through them. This all makes makes it difficult to imagine how you could be missing something important.

If you wish to not get stuck, seek to perceive what you have not yet perceived.

managing conflict is really about managing expectations. The earlier you set expectations with others, and understand their expectations, the better you can prevent situations where mismatched expectations result in conflict.

Laying out all of your internal, secret expectations is hard and uncomfortable because we do it so rarely, but doing so is important.

The best way to manage expectations is to keep everything in the open. The more transparent you are about everything, the less chance there will be that expectations are mismatched

At just 27 meters in diameter, Czepiela really didn’t have a lot of runway to work with, and at 212 meters above the ground, he had even less room for error. In order to achieve the landing, Czepiela practiced landing more than 650 times on a regular runway with a target painted on the tarmac.

“We needed specific wind direction and precise speed,” Czepiela said. “With too little wind and I wouldn’t be able to stop, too much of it would generate turbulence so intense that it would be tossing the plane, making me hit the building. Therefore, it was essential that we waited for the right conditions. In fact, flying entails 90 percent waiting and 10 percent hurrying, and this project wasn’t any different.”

The steel industry is accountable for about 7 percent of CO2 emissions globally. Its dependence on coal for the conversion of iron ore into its raw metallic form makes it incredibly challenging to decarbonize.

Helios has found that sodium may be utilized in place of carbon-rich coal.

Bender is a computational linguist at the University of Washington. She published the paper in 2020 with fellow computational linguist Alexander Koller. The goal was to illustrate what large language models, or LLMs — the technology behind chatbots like ChatGPT — can and cannot do.

The paper’s official title is “Climbing Towards NLU: On Meaning, Form, and Understanding in the Age of Data.” NLU stands for “natural-language understanding.” How should we interpret the natural-sounding (i.e., humanlike) words that come out of LLMs? The models are built on statistics. They work by looking for patterns in huge troves of text and then using those patterns to guess what the next word in a string of words should be. They’re great at mimicry and bad at facts.

We’ve learned to make “machines that can mindlessly generate text,” Bender told me when we met this winter. “But we haven’t learned how to stop imagining the mind behind it.”

People soon realise how much faster work can move through the system–how much sooner we can realise value–by moving the people to the work; rearranging people into teams aligned with these value streams.

For programme-scale product development—typically in the 50-200 person range—we run quarterly planning sessions where we review progress, align on direction and strategy, and set ourselves challenging goals using OKRs. We also use these sessions as an excuse to celebrate what we have achieved. Based on these new goals, there may be some movement of people between teams. Sometimes teams may disperse and new teams form as the profile of the work changes.

You can only do this if you understand all the different demands on the teams. Whether you model your product development work as features, epics, stories, experiments or goals, this still represents only one type of work, namely customer-facing delivery. Unless you can see all the competing sources of demand on the teams and on the organisation—and treat all of this as first-class work—you will continue to be disappointed that your expectations go unmet as all that unmanaged “ghost” work gets in the way.

Running engineering onboarding is optimizing two closely related problems:

1. How do we increase the percentage of engineers who are reasonably productive at three months?
2. How do we set the foundation that ends with more extremely impactful engineers a few years from now?

Done well, it excites new hires and raises the floor for success. Indeed, in rapidly hiring companies, effective onboarding is the highest-value investment you can make into engineering productivity

This project has enabled us to accurately classify a broad range of sensitive documents across the Adobe-wide SharePoint environment. In the future, we plan to grow this project by implementing more sophisticated ML models (such as BERT), continuing to expand our document categories, and extending our scanning capabilities to AWS S3 buckets and Azure storage blobs. We look forward to continuing our efforts in leveraging ML to help strengthen the security posture of our enterprise applications.

In one case, an executive cut and pasted the firm’s 2023 strategy document into ChatGPT and asked it to create a PowerPoint deck. In another case, a doctor input his patient’s name and their medical condition and asked ChatGPT to craft a letter to the patient’s insurance company.

there are really six “buckets” of team sizes. At each bucket, ICs + team leads need to operate a little differently in order to be successful within those teams.