Scott Genzer

Drag-and-Drop AI Run Huggingface on the Edge Only with @Altair

@elonmusk @4n4lisis correlation does not equal causation, @elonmusk . You should know this.

@4n4lisis SpaceX and Tesla have noticed a meaningful degradation in the capability of US college graduates over the past several years

Brilliantly said

this 👇

@DeputyGrocott I was a teacher for 20 years. I am now a data scientist at a software company.

What jobs do teachers go into if they stop teaching? Seen a few people coming out of the classroom but don’t see too much about what they do next?

@elonmusk image source: @yadvashem

@elonmusk There have been many forks in the road of human destiny. Some you choose. Some are chosen for you. Let’s try to remember the past so we choose to never repeat it. #NeverAgain

For the first time, there is a rocket that can make all life multiplanetary. A fork in the road of human destiny.

@rpilocator done - thank you!

@betty_bambam @JimBrowning11

My PC has been hacked!!!!!🤬

pretty good summary of what we should be focusing on in AI / ML in this world of insane hype…. newsletter.nocode.ai/p/supervised-l… via @armand_ruiz

oh no - nothing to worry about here… 🙄

@BrianTvenstrup good article - thx @BrianTvenstrup . I must admit I still cannot get my head around this new job of “prompt engineer”. Isn’t the whole point of LLMs like ChatGPT so that we can *not* spend time crafting queries / prompts / keywords?

Interesting thoughts about how the big data market is changing and what it might look like in the coming years: datasciencecentral.com/how-will-the-b…

@Merocle very nice unit

It's been a long journey. The UpBerry has taken its final form. It's a Raspberry Pi CM4-based device designed from scratch (different iterations in the photo). The case is made of aluminum. The main purpose is to display dashboards in the office, but other usage scenarios are certainly possible. Support 4k60. USB-C for power, connecting peripherals (via USB hub), or PoE Ethernet to USB-C adapter (for use without Wi-Fi). Power on by holding down the button (in a round hole next to USB-C) puts the device in bootloader mode, so there is no need to disassemble it to install an OS or change configuration. Other characteristics are from Raspberry Pi CM4: - Broadcom BCM2711 quad-core Cortex-A72 CPU - up to 8GB LPDDR4 RAM - up to 32GB eMMC Flash memory - 2.4 GHz, 5.0 GHz IEEE 802.11 b/g/n/ac wireless - Bluetooth 5.0, BLE P.S. I only made them for myself and our offices at my day job, but if this tweet gets a lot of feedback, I promise to do my best to start selling UpBerry. #raspberrypi #upberry

I should add huge kudos to @ClementDelangue for creating a freaking awesome platform for sharing + building AI/ML models. 🙏🏻

Drag-and-Drop AI Run Huggingface on the Edge Only with @Altair

@Rainmaker1973 I had the privilege of studying this papyrus as part of my masters degree, and was able to see it in person. It resides in the back archives at the British Museum, hanging on a wall covered w paper.

The Rhind Mathematical Papyrus is the oldest manuscript written in algebra and trigonometry, dating back to 3,550 years ago. It shows that the Egyptians used first-order equations, geometric series and a second-order algebraic equation, related to the Pythagorean theorem a² + b² = c² It also describes how to obtain an approximation of π accurate to within less than 1% and one of the earliest attempts at squaring the circle.

if you need a “prompting cheat sheet” for ChatGPT, doesn’t that defeat the entire point of ChatGPT? 🤔

Every Data Scientist needs to know these ideas. They will blow your mind. 1. Correlation vs Causation P(A | B) is the probability of A given B. It is the probability that we will observe A given that we have already observed B. P(A | do(B)) is the probability of A given do(B). It is the probability that we will observe A given that we have intervened to cause B to happen. In this context, an intervention simply means to take an action of some kind. Therefore do(B) means to take an action which causes B to happen. The expressions P(A | B) and P(A | do(B)) might seem very similar but they represent very different situations. 2. We can only learn P(A|B) from the data alone. Bob has an extremely accurate weather app and is always very good about bringing his umbrella when it rains. We observe Bob over several years and we find that whenever it rains, Bob always has his umbrella and he never brings his umbrellas on days when it doesn't rain. In the language of probability, we say P(Umbrella | Rain) = 1 and P(Rain | Umbrella) = 1 as well. What we can learn from this data alone is how to predict whether it rains with a 100% accuracy by checking whether Bob has an umbrella. We can also learn to predict with 100% accuracy whether Bob has an umbrella by checking if it's going to rain. What we cannot learn is what will happen if we give Bob an umbrella on a random day of our choosing. The answer to this question is P(Rain | do(Umbrella) ) and it's unknowable from the data alone. We need prior knowledge about how the world works to properly interpret the data we collected. We need to know that rain has an effect on Bob's behavior, but Bob's behavior has no effect on the rain. Information about the effects of interventions are simply not available in raw data unless it is collected by controlled experimental manipulation. 3. Scientific Experiments work because they produce a very special kind of data. You may have heard of what many people call a scientific experiment. Take a collection of objects, animals or people. Randomly split that collection into a control group and a treatment group. Apply your intervention to the treatment group while leaving the control group alone. If you observe any differences between the treatment group and the control group, it is logical to attribute these differences to the treatment. You can therefore say the differences were caused by the treatment. In statistics, the procedure I just described is called a Randomized Controlled Trial. It is a procedure for generating a specific kind of data where: P(Difference | Treatment) = P(Difference | do(Treatment) ) This is why traditional science experiments work. They are designed to capture causal information. This is not the case for vast majority of data that we collect in society. Without human guidance or access to real world knowledge, statistical algorithms and artificial intelligences can only learn P(A | B) from the raw data. This is a fundamental mathematical limitation on the use of data alone. That's it for now. This post is part of a series of posts about the concept of causal inference. They are based on the content of the Book of Why by Judea Pearl with lots of commentary from me. Follow me (@kareem_carr) so you don't miss out on the next post. Please show support by liking and retweeting the thread.

Interested in optimising your manufacturing operations? This @Altair webinar will inspire you with some real-life examples. #AI #Analytics #manufacturing web.altair.com/unlocking-manu…

thank you @mgualtieri - finally someone talking sense! 👇

@EdKrassen As an American genealogist, I look at ship manifests filled with immigrants every day. Only 3 things look different now than 100 yrs ago: (1) they came from Europe instead of South America, (2) we admitted most of them upon entry at Ellis Isl., (3) they came to NY instead of TX.

New York City Mayor Eric Adams just unleashed on the immigrant problem at the Southern Border. Mayor Adams said: “I’m gonna tell you something New Yorkers, never in my life have I had a problem that I didn’t see an ending to. I don’t see an ending to this… This issue will destroy New York City. Destroy New York City.” He then went on to say, “Month after month I stood up and said this is gonna come to a neighborhood near you. Well, we’re here, we’re getting no support on this national crisis, and we’re receiving no support.” Regardless of our political views, I think all Americans are concerned about immigration in the US. The problem, however, isthere is no solution that is both just and humane while also making sure that immigration doesn't effect us negatively. How do we fix this issue? I don’t want to hear your attacks on one politician or the other. I want to hear your thoughts on how the problem is fixed. What are your thoughts?

@nateliason @ingomierswa

Has anyone made a good AI tool yet where I can load in everything I've ever written, every podcast I've recorded, every note I've taken from a book, and then have a ChatGPT-esque interface where I can query my past self? I'd probably pay hundreds of dollars a month for this.