Ningo

Resides in the land of the Courageous and Curious.

[Ningo @Fresh_Penguin1]

There is technology, then there is TECHNOLOGY. Advanced Semiconductor Materials Lithography is the quintessential of the latter.

Based in Veldhoven, Netherlands, Europe's most valuable technology company finds itself at the center of the chip war between China and the USA today

[Sdudla Mafehlefeezy♥ @lulu_luwela]

When recreating your childhood memories is progress.

Those little kids on a couch in the Transkei are now:
Microbiology and strategist, MBA candidate
Eco & stats, MBA
CA, CFA

My parents didn’t miss.
This is the dream our parents envisioned for us. We are living it 🩷

[Ningo @Fresh_Penguin1]

@just_Enhle07 😂

[Ningo @Fresh_Penguin1]

@First_alphas 😂

[Dario Amodei @DarioAmodei]

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.

It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.

The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).

More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.

In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.

Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.

I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

[Ningo @Fresh_Penguin1]

@SpecialSitsNews 😂

[Ningo @Fresh_Penguin1]

@uMaster_Sandz 😂😂

[Ningo @Fresh_Penguin1]

@atletienglish 😂

[Mamelodi Sundowns FC @Masandawana]

Another piece of Masandawana history! ✨

#Sundowns #FIFAIntercontinentalCup #NeverStopRising

[Ningo @Fresh_Penguin1]

@snap_vino 😂

[Ningo @Fresh_Penguin1]

@gugulethup_ @NtombiTurquoise 😂

[Ningo @Fresh_Penguin1]

@tumeloditle @Masandawana She knows ball!

[TwoStar Sundawana 🌟🌟 @symps247]

While searching for motivation, the chairman of the best team in Africa said I got you! 👆🔥

[Ningo @Fresh_Penguin1]

@SportsStooge10 😂😂

[Trung Phan @TrungTPhan]

Nike's market cap hit a peak of $280B in November 2021. It's now down to $57B (a $223B drop) and will be delisted from S&P 100.

Former Nike branding exec Massimo Giunco wrote a viral post in 2024 laying it all out. He blamed CEO John Donahoe (2020-2024) for going all in on direct-to-consumer (DTC)...with a cameo from McKinsey:

▫️ELIMINATE CATEGORIES: McKinsey advised Nike to get rid of categories (running, basketball, soccer) and re-classify everything into “Women”, “Men” and “Kids”.

The logic was that Nike was duplicating resources and a pivot to DTC would provide enough customer data to inform product decisions instead of relying on the category experts (eg. a basketball vet that spent 20+ years at Nike). A lot of these experts were fired and Nike lost their insights.

This was a clear L because Nike quietly brought back categories at end 2023.

▫️END WHOLESALE LEADERSHIP: Nike ended hundreds of relationships with wholesales partners and prioritized Nike's website over retail.

The change looked genius during COVID but as customers returned to brick ‘n mortar, Nike’s product were nowhere to be found. It had burnt bridges with partners, who were happy to give shelf space to upstarts (this wasn’t covered but I think On and Hoka took advantage of this for running)

There was also a lack of feedback from retailers, which led to inventory issues (the “data-driven” insights from online sales proved to not be a panacea).

▫️PRIORITIZE DIGITAL MARKETING: Nike changed its marketing budget to focus on driving users to Nike digital properties and membership platforms.

For decades, Nike spent 10% of sales on brand advertising to create an aspirational halo. The prioritization of programmatic ad spend meant Nike went from “create demand” (new customers) to “serve and retain demand” (re-targeting existing ones).

The result was a slowdown in sales.

“Because of that,” writes Massimo Giunco (who spent 21 years at the company), “Nike invested a material amount of dollars (billions) into something that was less effective but easier to be measured vs something that was more effective but less easy to be measured. In conclusion: an impressive waste of money.”

The quality of advertising was also...not great.

***

The focus on DTC is not surprising. Donahue was formerly CEO of B2B SAAS firm ServiceNow.

Nike’s DTC business peaked at 44% of sales in 2024 (vs. under 30% before the strategy change).

The digital focus seems to have commoditized the product, impacted Nike’s brand perception and created an opening for competitors.

***

Original post: https://t.co/EAROAHEZRM

[Lawrence @iKillCuriosity]

Family Feud/U Don’t Know

Jay Z was just sliding on these transitions.

[💎🍾 @TheRocSupremacy]

& he did it knowing she hates attention 😂

He said “she’s gonna kill me for that one… but whatever” 😂😂😂

[Ningo @Fresh_Penguin1]

@zeeontv 😂😂

[Ningo @Fresh_Penguin1]

@pookiepolls 😂😂

[Ningo @Fresh_Penguin1]

@Twenty9United 😂

[𝐟𝐞𝐝𝐞𝐯𝐚𝐥𝐯 @fedevalv_]

The full buildup to Real Madrid’s 3rd goal.

Jose Mourinho ball is back 😭😭🤍 https://t.co/fztazzgnbq