Shaker Cherukuri

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Shaker Cherukuri

Shaker Cherukuri

@ProcessISInc

Agentic Workflows, Root Cause & Gap Analysis, AI Systems Engineering. Carbon in the Agentic loop. Golf & Travel. #IU #UofL $CMI $CAT $GE $GEV $BAH

Beigetreten Haziran 2009
171 Folgt831 Follower
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Shaker Cherukuri
Shaker Cherukuri@ProcessISInc·
How Jet engines are powering Data Centers? $GEV GE Energy and $GE GE Aviation synergies would have created an epic combo right now for AI datacenter power needs with the Turbines design, manufacturing and supply chain scale and scope for Gas turbines and Jet Engines. They are separate companies now unfortunately. Caterpillar $CAT mentioned in this article owns Solar Turbines which manufactures industrial gas turbines for power generation. Cummins Inc $CMI not mentioned here has a power generation business that sells mostly diesel generators. The engine business for Cummins and Caterpillar sell the diesel engine to the power business and also other sectors like trucking, off highway, marine etc. Those sectors are also seeing demand boost from this AI datacenter buildout. GE Vernova Energy is also seeing a huge demand surge for it heavy duty gas turbines for the grid and microgrids for the datacenters. I worked at these companies in the past. Interesting to see this play out. The stock valuations of these firms are at all time high and still rising. Picks and shovels of AI datacenter buildout. wsj.com/business/energ…
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Secretary Sean Duffy
I am on my way to LaGuardia Airport now in response to last night’s horrific crash involving Air Canada Express 8646 and a fire truck that killed two pilots. @FAANews and @NTSB are working closely on this, and we will share updates as soon as possible. Please keep the victims, families and response teams in your prayers.
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Brett Adcock
Brett Adcock@adcock_brett·
I’ve been hiring for 20 years and I’m batting .000 when hiring senior ppl from big established companies. It doesn’t work
Machine Pulse@machinepulse_

What do billionaires optimise for when hiring? @adcock_brett founder of Figure AI discussed what he looks for in a hire on the WTF Online Podcast: "I think the conventional wisdom is to go out and hire somebody really experienced, that makes you feel really good, from a really good background, at a successful company. And I found that playbook is just complete crap. Throw that right out the door. Even now, Figure has gotten to a point where we have these big shots knocking on our door wanting to come work here, from big companies and wherever else. But it's just not the right approach. If you look at every generational company, it's not like they went out and picked the VP here and the VP here and the VP here and put it together. It's like the opposite of what Meta is doing right now. Look at Meta's superintelligence lab. It's like putting 15 Tom Bradys together and making that work. It's just immediately going to collapse. It's not going to work. My view is you just need to find people that really care. That's the core axiom of what I look for in talent."

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Shaker Cherukuri
Shaker Cherukuri@ProcessISInc·
@ClayTravis We Always drive from Nashville to any trips to north, east Coast or south in the US. Fly only for west coast, or Overseas
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Clay Travis
Clay Travis@ClayTravis·
4:30 AM in New Orleans and it was already a multi-hour line. Just met guy in Nashville airport who said a friend decided to drive six hours because it was faster than waiting in line at New Orleans. Democrat airport disaster:
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The White House
The White House@WhiteHouse·
🚨 President Donald J. Trump calls for a pause on all military strikes against Iranian power plants and energy infrastructure for a five-day period, subject to the success of the ongoing meetings and discussions.
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Shaker Cherukuri
Shaker Cherukuri@ProcessISInc·
@BillDA I found I don’t need a dehumidifier. Fixed the root cause fixed the problem
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Bill D'Alessandro
Bill D'Alessandro@BillDA·
I was quoted $10,000 to install two dehumidifiers in my crawlspace. I saved $7,500 by designing a DIY custom crawl space dehumidification system with Claude 🤑 I am not an HVAC professional. Here’s how I did it. Our story begins with the discovery that our new home needed a dehumidifier installed in the crawl space to prevent mold. The professionals told me it would cost $10k, since I’d need one unit on each end due to the size of the space, plus a second drain line installed. “Can’t we just use fans to move the humid air from one side toward the dehumidifier?” They wouldn’t do that. Enter Claude… I uploaded a floor plan of my crawl space and air volume dimensions, telling Claude what I was trying to do. It researched the best dehumidifier sized appropriately for my air volume (100 pints apparently). Found me the best price - $1,500. Now it was time for fans 💨 I had originally envisioned the single dehumidifier at one end of the space, with fans on the opposite end. Claude taught me that would just draw more moist outdoor air in through the vents on that side, creating a linear flow through the crawl space. Instead it modeled the air flow and suggested a circular vortex with 4 fans, one on each wall, in a circle. That sucks in minimal outdoor air, keeping cool dry air circulating. I told it to research appropriate fans. It found four 20” sealed bearing fans on Amazon (impervious to dust), with DC drive motors (more energy efficient than AC apparently). $120 each. 🔌 It told me to buy a smart plug for each fan and a few internet connected humidity sensors. Another $200. Claude mapped where to install everything in the crawl space. Here’s how it works - the humidity sensors monitor the crawl space air continuously. If it ever exceeds 60% humidity, the smart plugs switch on all 4 fans, circulating the air in the crawl space past the dehumidifier until the humidity is below 50% 🔃🔃🔃 Total cost ~$2,500 for everything and one Saturday of work for me. I saved $7,500 vs. the original quote because I didn’t need two dehumidifiers, and Claude tells me my version is nearly twice as energy efficient. Plus I learned a ton about my home and had fun. I didn’t know anything about dehumidifiers, fans, or air flow dynamics before starting. AI can do so much more than write code - the applications are endless.
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Tom Goodwin
Tom Goodwin@tomfgoodwin·
It’s hard to underestimate how smug Apple is going to be about this in 3 years time. Why on earth did people with zero right or need to do this, pile in. Google I get Amazon -sure Facebook - you sell ads against stuff people provide you for free.
dax@thdxr

you're probably underestimating how crazy things are

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Maurizio
Maurizio@themgmtconsult·
Aside from some clear, well-known exceptions, what is commonly defined as a "strategic business genius" is often just a lucky gambler with a good PR department. In the consulting, startup and corporate worlds, we have an obsession with the narrative. When a deal closes or a quarter goes phenomenal, the post-mortem is almost always a neatly packaged story of "perfect execution" and "visionary decision-making." We strip away the noise and the luck until all that's left is a heroic tale of C-suite competence. But if you look closer, there's more to the story. There is a hidden graveyard of identical strategies that failed simply because the coin landed on the wrong side. A book that completely changed my life and my approach to work is "Fooled by Randomness" by Nassim Taleb. In that book, Taleb talks about Mediocristan and Extremistan as two ways of engaging with the world: linear and non-linear. Most people treat professional life as "Mediocristan." They think if they put in 10% more effort, they get a 10% better result. While a standard management job might look linear on paper, the reality of, for example, consultative sales is a series of "micro-Extremistan" events. A high-stakes deal is a binary outcome. You either get the contract or you don't. Zero or one. It doesn't matter how "perfect" your slide deck was if a random budget cut at the client kills the project in the 11th hour. This reality sometimes leads to a dangerous paradox in our sales processes: how do you qualify deals? We are taught to be rigorous. We use frameworks to filter out anything that doesn't "make sense" on paper. But strict qualification can become just a filter for the status quo. If you only chase deals where you have a clear edge, an existing relationship, or a "perfect fit," you are effectively optimizing for the middle of the bell curve. When you only play it safe, you yield the high-ground to incumbents. You never win the transformative new customers because, on paper, those deals look "unqualified." To counter this, you may want to look into something Taleb (him again) talks about at length: a barbell strategy. You don't just "play it safe" or "go for broke." You do both: 1) 90% Rigorous, hyper-qualified consultative sales. These are your bread-and-butter deals that keep the lights on; 2) 10% "irrational" bets. The deals that don't make sense on paper, the incumbents you shouldn't be able to unseat. Allocate a portion of your effort to these "unqualified" opportunities. Most will fail (fixed downside), but the one that hits will be the one the C-suite writes their next "heroic narrative" about. When we reach a good business outcome, we tend to over-attribute it to our own alpha. Nowhere is this more prevalent than in the sales process. You think a "Win" validates every tactical choice you made; in reality, you can do everything wrong and still win (Luck), or you can do everything right and still lose (Variance). In consultative sales, the goal is to maximize the Expected Value of your time. You have to treat every lead as a bet: a) Fixed Downside: The cost of the discovery calls, the research, and the relationship building. This is capped. b) Uncapped Upside: The massive, multi-year contract that makes the big bucks for the entire firm. My recommendation is always to treat sales as a stochastic process rather than a linear chore, so you detach your ego from the "No". This way, you realize that a rejection isn't a failure of your "narrative" but rather a data point in a larger probabilistic set. Your post-mortem must answer the question "Was the quality of our bet correct?" and not the more common "Why did we lose that deal?" If you made the right move based on the information you had, and you still lost, that is a successful process. Over a long enough timeline, the randomness washes out, and the quality of your process is the only thing that remains.
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NTSB Newsroom
NTSB Newsroom@NTSB_Newsroom·
The NTSB is launching a go team to investigate the March 22 Jazz Aviation, Air Canada Express Flight 8646, CRJ900, airplane that collided with a fire truck on Runway 4 at LaGuardia Airport in New York NY. Chair Jennifer Homendy will serve as the on-scene spokesperson, accompanied by Member John DeLeeuw. The investigative team is expected to arrive today. Follow @NTSB_Newsroom for updates.
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Mark Cuban
Mark Cuban@mcuban·
We directionally agree. ✔️ Where we disagree is that employees will fully share, or even accurately share .their “corporate knowledge”. They are protective of that knowledge. Most of which is not documented anywhere. That’s their “edge”. They certainly aren’t going to share that with any system they believe to create a threat(s) to their job or future. Humans know they have an expiration date. AI doesn’t believe it expires. As far as “recursive”, I realize some see this as the holy grail and future of AI in companies, I think it’s great for anything with specified processes or anything built on math. Anything recursive that touches strategy will be a problem for a company. Why ? Because even though all companies will use different data, the results of recursive systems will start to look very similar to each other, diminishing any competitive advantage. AI is a “leapfrog” business. Much like software was back in the day. Every day, week, month, there are new features. You know this better than anyone. You are in a race But they all tend to end up in 90pct the same place. With that 10pct value being the reason why customers pick one over the other. Point being, that in early days the products seem very different. Over time they will be less and less so. Early adopters get an edge. But that edge dissipates. Being recursive isn’t the advantage it was expected to be We saw this with NBA analytics. When the Mavs were the first team to use analytics for everything, we had a huge advantage. We could trick teams into playing their worst lineups, because they didn’t even know what their worst lineups were Today, analytics have become an efficient market in the nba. Everyone has pretty much the same output and values per shot type. And, use the same or similar systems to get there. But players, like employees in enterprises, figured out what metrics they had to outperform to differentiate themselves. They learned to draw more fouls. To create and make mid range shots at a better percentage, because they knew that would be what defenses left open. Business is no different. They have to anticipate that in the next 5 years or so, everyone will have the same tools, info and knowledge, with deltas on the margin Which is exactly what has happened with every new tech. Over time the same shit is available to everyone. The early adopters, that iterated and executed the best, were the winners All of which is why I’m not a doomer. Why I don’t think there will be mass unemployment. The only layoff trigger will be upstart, native companies replacing incumbents. Or more likely get acquired by them. That’s the way I see it. But I could be wrong 🤷🏼‍♂️
Adam.GPT@TheRealAdamG

Very aligned. A few comments: 1. I think repaving and reinventing have a big Venn diagram overlap. I have gravitated to the word repaving to mean that the workflows that exist today in software will be reimagined via a first principals as AI stitched other with software as glue between the inputs and outputs of models. 2. The other part of this is data. Information and knowledge are both data problems. Human and systems data need to be integrated. Systems get connected with a semantic / metadata layer (aka not moving data, but integrating it so agents can access it). Here is what we did internally (openai.com/index/inside-o…) and those learnings + what our FDE teams learned are directly informing the “business context” layer of our Frontier platform (openai.com/business/front…). As for human data, that’s where the strength of the models + top down executive buy in are unlocking Enterprise customers is allowing for the accelerated mapping of things. Whether it is tribal knowledge, undocumented processes or legacy systems — today’s models (audio, visual understanding, computer use, etc) can be used as tools to ingest, break down and “understand” that human data and bring that unstructured data also into the context layer. Then you hill climb. With data connected, just like with “memory” in ChatGPT, there will be “organizational memory” for co mpanies. That will start to have a compounding effect. While we don’t have recursive systems yet, I think you start to get something that feels like. 3. Not doing this or some version of this is not an option. Some will lead and some will follow, but I think this new world we are going into is the real “digital transformation”. The internet and what got built on top of that was transformative, but I think it would look small in hindsight. However, it was an absolute prerequisite to get everything connected (as infra) to then layer on intelligence. As John Chambers used to espouse: “the network is the platform”. He was right, but also wrong where the value accrues. Companies will have no choice or they’ll just find themselves to be slow, laggards and under massive margin pressures. Things will just get “repaved” with AI as the substrate. I think we’ll see the first big waves of early adopters move at scale in 2026.

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Camus
Camus@newstart_2024·
Bryan Johnson (the guy spending millions to reverse aging) dropped his 5-sentence anti-aging diet: “Lentils, vegetables, berries, nuts, seeds, extra virgin olive oil. Avoid sugar, processed foods, fried foods, additives, and anything you can’t pronounce.” Bonus rule: He eats everything in a 6-hour window (last meal at 11 a.m.), then fasts 18 hours straight — says it’s the key to his elite sleep. Time-restricted eating (like his 6:18 pattern) improves insulin sensitivity, reduces inflammation, and boosts autophagy — all linked to slower biological aging in human trials. Do you eat in a tight window like this? Or do you think it’s too extreme for real life? Your take 👇
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Shaker Cherukuri
Shaker Cherukuri@ProcessISInc·
@BdrooDr @davidasinclair Age related improvement is common I was told. Eye ball elongation reduction with age. Could also be all the outdoor time spent golfing in last decade or so
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David Sinclair
David Sinclair@davidasinclair·
Eye fact 👀: ~80% of people over 45 have reduced focusing ability & according to Japan’s Dr. K. Tsubota, the lack of violet light hitting our retinas, in part due to doctor’s recommendations to avoid sunlight, is a major cause of vision loss with age research-highlights.keio.ac.jp/2019/07/b.html
David Sinclair@davidasinclair

Every week, I tell one of my students to increase the font size on their slides, especially numbers. Here’s how you know you’re good: Take 5 steps back from your laptop or monitor. If you can still read every letter & number clearly, you’re probably good 👍

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