communication 10

Our brains remember some things better. Explaining that way makes it stick. Here are the eight things, most important first, that help you: Structure explanations memorably: Face. You remember faces before facts. So cast characters: “Imagine you’re a courier carrying a packet.” Prefer archetypes to real names — less baggage, more imagination. Place. You’re reading down a list now — and the top feels more important. That’s spatial wiring. Turn any concept into a map. Use higher, deeper, nearer, inside, … Tale. You read #1 and #2 first because they came first. Your brain built a cause from that sequence. Time creates cause for free. “Because” makes anything believable. Scale. “Two feet tall” lands instantly. “60 cm” forces you to convert. Your brain doesn’t measure — it compares. Give it reference objects, not just numbers. Deliver explanations memorably: ...

This week, I learned: Radio free Xp podcast. Nudge 61 always announce first before doing. Give people time to plan comment and react. That gets you alignment without sacrificing freedom. give information, not orders. When someone is parking a car, tell them how much space they have, don’t tell them to start stop or how much to turn left it’s almost impossible to change the culture if you’re not the boss

Every time I get annoyed at people, I remind myself to be more like ChatGPT. Specifically: Don't get annoyed. Be patient. Encourage them. Step back and show them the big picture. (Then I get annoyed at myself for getting annoyed.) Today, I analyzed how exactly ChatGPT is different from me. So, I took a pitch document I co-authored with ChatGPT. Section A: Authored by Anand WHAT DO WE NEED? ...

This week, I learned: Dockerfile can have FROM scratch and you can add specific binaries rather than an entire OS. via Fine-tuning session by Dan. Notebook Example of fine-tuning Mistral. Consumed 28 computes ($2.8) Axlotl is what the top fine-tuned LLMs are trained on Deepspeed provides distributed training Flash attention lets data stay on GPU Sample packing packs samples of different lengths into equal length tensors Visualize the RANK of a token in a generated stream instead of logprob The Knowledge Project. Tomorrow Gayner What I’d like in my obituary: Anand was happiness. A guru. Generous. To get what we seek we must deserve this. Build, measure, learn If you did the same thing daily for 50 years, would it be a great thing? If yes, do it. If not, stop. Do this in daily retrospectives My new role should be productivity through technology innovation. That may mean a CTO role. But be specific otherwise no one will understand it Hidden brain podcast. Us 2.0. Win hearts, then minds When in an interaction, ask yourself. Can I learn and change myself? Can I win their hearts, then mines, so their behavior will change. That identity will change Notice when you get emotionally triggered. That’s exactly when you should not get emotionally triggered Try model humility and moral Look for close to people’s identities in our conversations. What are things they like? What does it mean for them? Simply ask. With that understanding of identity, it becomes easier to reframe things in a way they will understand Bard can talk to Gmail and Google Drive! #PREDICTION As automation takes over these mainstream activities, people will take over the niches. Since expertise like knowledge is fractal, there will be many more segments of one in the future and it will be easier to automate clusters of similar abilities. Recommenders and brands will become even more important Stephen Osserman’s Observables have some nice notes. Visualizing partial election results D3 Force Dilemmas: Data Distortion Sandra Becker’s 30 day D3 course

Microsoft ported its PowerPoint Speaker Coach to Teams. Since September, it’s given me suggestions covering 11 hours in 77 calls (I speak ~10 min/call.) I say “uhh” a lot. That’s intentional I use the filler word “uhh” in 70% of my calls. That did not surprise me. I do that intentionally. On a poor network, they know I’m still connected They know I’m going to say something I sound less confident. That invites critique I can learn from But I also use filler words like “You know” and “I mean” in half the calls, and “like”, “actually”, and “basically” in a fifth. That’s NOT intentional, and I’ll be conscious. ...

In a number of sessions I’ve been to, people ask analysts to make their results more interesting – to tell stories with them. I’m co-teaching a course, part of which involves telling stories with data. So this got me thinking: what is a story? How does one teach storytelling to, let’s say, an alien? Consider this mini-paper. ABSTRACT: Meter readings exhibit spikes at slab boundaries. We also find significant evidence of improbably events at round numbers. Electricity shortage is a serious problem in most Indian states. Part of this problem is due to the inaccuracy of reporting procedures used in monitoring meter readings. Our focus here is not to document or experimentally determine the degree of inaccuracy. We have adopted a data driven approach to this problem and attempt to model the extent of inaccuracy using basic statistical analysis techniques such as histograms and the comparison of means. Our dataset comprises of the frequency analysis 12-month dataset containing monthly meter readings of 1.8 million customers in the State of Andhra Pradesh. We find that a histogram of these readings shows unexpectedly high values at the slab boundaries: 50 (+45.342%, t > 13.431), 100 (+55.134%, t > 16.384), 200 (+33.341%, t > 15.232), and 300 (+42.138%, t > 19.958). We also detected spikes at round numbers: 10 (+15.341%, t > 5.315), 20 (+18.576%, t > 6.152), 30 (+11.341%, t > 4.319). The statistical significance of every deviation listed above is over 99.9%. Further, every deviation has a positive mantissa. This leads us to confidently declare the existence of a systematic bias in the meter readings analysed. You’re probably thinking: “I know why he’s put this example here. It must be a bad one. So, what a rotten paper it must be!” ...

Telecom Italia’s Gandhi ad.

Darwin’s 10 rules for taming e-mail. I badly need this. I am not often in office, and don’t have a fast way of checking office mail through the Web either. Tips 5 and 10 on the list (“avoid e-mail multipliers” and “use the telephone”) are next on my agenda for drastic e-mail slashing.

Effective networking.

Punctuation is critical. Believe me, mistakes can be glaring!