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Can the Yankees ride these two new young players into October?

Let Emma Frost be problematic!

A mother and son got a shocking surprise when a DNA test revealed he had nine half-siblings, all of whom were genetically connected to his mom's former gynecologist.

Thousands of newly obtained messages from Dr. Anthony Fauci’s government phone are offering a new look at his private discussions during the COVID vaccine rollout. One exchange about a theoretical concern involving vaccination, fever and pregnancy is drawing fresh scrutiny on Capitol Hill as lawmakers compare Fauci’s private conversations with his public statements at the...

Happy-faced spiders are found in highly elevated and damp environments.

Democrats Shocked By The Cancel Culture They Built

Authored by Sasha Stone via SashaStone.com,

I've heard the new talking point on the Left trying to explain away Hasan Piker's truly vile comments on 9/11. Bernie Sanders, AOC, and Abdul Sayed have all used the term. The memo went out, and now they're repeating it like parrots. You can see for yourself in these videos [click on SashaStone's blog above to see a montage].

CNN: “Hasan Piker said America deserved 9/11. Are you comfortable with that?”

Bernie Sanders: “No, I think that was a dumb statement. But he has lots of followers. We have to get above cancel culture. We need a big tent.” pic.twitter.com/uk92aL1z40

— TheBlaze (@theblaze) August 5, 2026

El-Sayed on Hasan Piker: To sit here and play gotcha politics with a dumb thing somebody said out of context…I want to be held accountable for what I say and what I do rather than this idea that we're so stuck in cancel culture that all of us agreed was a bad idea back in 2020… pic.twitter.com/88OUSzIQLM

— Acyn (@Acyn) August 9, 2026

We'll hear it every time someone brings up Hasan Piker: "We have to get over cancel culture."

I almost fell off my chair. Now they're noticing cancel culture? Now they want to end it just so they can snuggle up to one of the most vile people in the influencer lane because he has a lot of followers?

Cancel culture is not over on the Left. I'm living proof as someone who was canceled and is still canceled. If they want it to be over, then let it be over - but it is most certainly not over. All of these monsters are still carrying pitchforks and screaming at the Right, calling them "racists" and "bigots" and "transphobes." None of that has gone away.

Why do they think no one showed up at the America 250 celebration or would play the Kennedy Center?

Taylor Swift allows her music to be played by everyone except you-know-who. She is saying that Trump and his voters can't be included in her world. They were celebrating on TikTok over it - another cancel culture battle won. And they mostly win them all.

They still have all of the cultural power, and they'll decide who gets to stay or who has to go. That decision will be based on one thing: conformity. If you go along with it, you can stay. If you push back, you have to go.

Sophie Cunningham made news recently just for stating that she believes in biological reality, and it turned into a major scandal driving the news cycle for weeks.

Even if she wasn't thrown out of the WNBA, which is progress, I suppose, that doesn't mean she hasn't been punished and will continue to be punished. They can't cancel J.K. Rowling either, but the enormous pressure she's been under for years proves exactly who these monsters are.

The Paramount/Skydance merger with Warner Bros. shows just how far and wide cancel culture is still used as a method of societal control on the Left. All of Hollywood, all the celebrities, the New York Times, and the trades are pummeling the deal for one reason and one reason only: Donald Trump.

The actor Geno Segers can sing. He can really sing.

But because some children spies went out and hunted down his comments on trans ideology - and the fact that he dared to mock Don Lemon - he was thrown out of Hadestown.

Don't tell me cancel culture is over. It is not. I am still on the outside of the Left's totalitarian Doomsday Cult, and it will likely stay that way until I leave this earth. They're not giving it up. They're just pretending to because now they have a "problematic" creep causing them problems.

It was, in fact, AOC who backed the whole concept of "deplatforming."

Hasan Piker likes to be controversial, just like Candace Owens, just like Tucker Carlson. They say things to provoke people for clicks and views. There is nothing new about any of this. The difference is that the Democrats are allowing this one guy to get a pass because if they turn on him, he'll turn on them.

And lest you start in with "there's cancel culture on the Right, too" - not really. It's true that people are attacked and sometimes exiled for their views, but the Right does not have the same kind of power the Left does.

I was canceled because of a joke on X that they deemed "racist" and for voting for Trump. These are not cancelable offenses in my view. But public shaming is sometimes necessary to push back on someone who, for instance, claims Israel murdered Charlie Kirk.

I would love it if cancel culture was really over, but it isn't. These Democratic Socialists are lying. They aren't giving up their most powerful weapon against the Right: that they own everything and run everything in most of our culture and our institutions.

They have been abusing that power for ten years. I, for one, am happy to see it splash back on their faces like toilet water. They deserve it.

If cancel culture is over, let it be over. Give up your power over all of us to decide who can say what and what people have to believe. Let's all be one country again. Every person who voted for Trump knows how they're treated by most of our cultural overlords every single day for ten years.

End it, and then we'll stop talking about Hasan Piker.

Tyler Durden Tue, 08/11/2026 - 07:20

On Monday, the 45-year-old "This Is Us" alum clapped back at "judgy" people whose criticism of her decision "doesn't matter."

On Monday, the 45-year-old "This Is Us" alum clapped back at "judgy" people whose criticism of her decision "doesn't matter."

"They ask my hosts, 'Are we going to be the millionth?' They try to bribe the servers."

It has been so bad for so long that Boone cannot just blindly write their names into the lineup and/or stick with them late in games.

The Oscar winner revealed that he had started drinking again during a wide-ranging interview with Esquire published Monday.

The Oscar winner revealed that he had started drinking again during a wide-ranging interview with Esquire published Monday.

China's Unitree Robotics IPO 5,526 Times Oversubscribed By Retail Investors

Unitree Robotics' initial public offering was heavily oversubscribed (5,526 times) by retail investors as China's first publicly traded humanoid robotics company prepares to enter the public markets. The IPO will help usher in physical AI to the equity market.

The Hangzhou-based humanoid robot maker raised about 6.1 billion yuan, or $904 million, after selling 40.4 million shares at 150.8 yuan each, according to Bloomberg.

The offering values Unitree at roughly 61 billion yuan, or $9 billion, ahead of its expected STAR Market debut this month. The IPO will make the firm China's first publicly traded humanoid robot manufacturer.

Top investors soaked up about 20% of the offering, including AI startup DeepSeek, a Tencent-affiliated investment vehicle, and investment arms linked to CNPC, China Southern Power Grid, and China Telecom. DeepSeek was allocated a 2.31% stake.

China Dominates The Humanoid Robot Race. Can Trump Close The Gap?

It should surprise no one that new data from Smart Analytics Global, cited by Bloomberg, shows that Chinese humanoid robot makers accounted for a staggering 97% of global shipments in the first half of 2026.

The figures come as the Trump administration increasingly recognizes that humanoids will be critical to the emerging physical AI era, creating an urgent need to build out America's robot supply chain, including motors, actuators, sensors, batteries, and AI models.

via Barclays.

Smart Analytics Global said global humanoid shipments tripled to 19,100 units in the first half from 5,100 a year earlier. The research firm expects deliveries to reach roughly 60,000 this year and climb to 500,000 by 2030.

The estimates are similar to those from major institutional research desks, including UBS, whose most bullish forecast projects nearly 400,000 global deliveries by the end of the decade.

via UBS. 

Our latest notes dissecting the humanoid robot value chain and examining how to profit from the key companies that manufacture critical components, such as motors and actuators, find that many of these companies are based in Asia, more specifically in China.

• Physical AI Faces One Critical Chokepoint, And Here's How To Profit
• Digging Deeper Inside Physical AI's Hardware Stack Powering Humanoids

China's dominance on humanoids reflects years of policy support and government funding aimed at accelerating robotics, drones, electric vehicles, and much more. The country's progress was on display at the World AI Conference in Shanghai last month, where dozens of companies demonstrated rapid advances in dexterity, speed, and autonomous capabilities. 

The US recently banned imports of new Chinese humanoid and quadruped robots, as well as certain components, citing national security concerns and cybersecurity risks to AI infrastructure. 

The Trump administration has yet to release a standalone executive order specifically aimed at supercharging the domestic humanoid robotics industry, but we expect that could be coming.

Tyler Durden Tue, 08/11/2026 - 06:55

The Brooklyn native explains why the city's biggest hassles are actually everyday opportunities to build strength, balance and endurance.

As much as fans may have wanted to see the Nets take a big swing, this wasn’t the right time.

Everything You Wanted To Know About Building A Cheap AI Setup (That Still Works) But Were Afraid To Ask

Authored by Christopher Penn via 'Almost Timely News' substack,

I’ve been putting together a new course for Trust Insights, AI for Writing (and Writers), which will be coming out August 25th, and during the process of creating that course, I realized I’ve never walked through setting up a discount agentic AI system.

For a while now, many of us who work in “corporate” have had access to what feels like unlimited amounts of AI (though that free ride is coming to an end at enterprise shops thanks to absurdly large bills). For the average person who doesn’t have the backing of a corporation, how could we tap into the power of agentic systems without tapping out our wallets?

This tracks back to a question from Leslie in the Analytics for Marketers Slack group:

“have you done a video or post with recommendations for a cheap second computer set up someone can use to build their separate AI machine?“

So this week, let’s get scrappy.

Warnings, Disclaimers, Disclosures

If you work at a company, please check with IT before installing software willy-nilly. As a former IT professional, we thank you.

Second, in this issue I’ll be talking about Chinese-made AI models like Qwen and DeepSeek. There is a HUGE difference between a Chinese model hosted by a company in the People’s Republic of China (PRC), and a Chinese-made model hosted by a company outside the PRC.

It is manifestly unsafe to use any AI models hosted in the PRC for any kind of confidential information, period. Totally fine to use those models for things that are completely public, like research requests.

However, it is completely safe to use Chinese-made AI models on your own hardware, or in an infrastructure that’s trustworthy. There are many, many great inference providers that have things like Zero Data Retention (ZDR) hosting which are even safer to use than Big Tech models because the providers warrant that they don’t keep your data at all. (Most Big Tech providers have a “we hold onto your data for 30 days to prevent abuse” clause in their Terms of Service)

There is a lot of fear mongering about open weights models (including the Chinese ones) happening right now because Big Tech providers’ profits are on the line if these models continue to offer parity of capabilities at a fraction of the cost. Don’t believe the hype; open weights models are so safe that companies like HuggingFace have used them to do their own cybersecurity defenses.

Third, where I have commercial relationships, I’ll disclose them. I have an Amazon affiliate link in this week’s article, and obviously I work for my company, Trust Insights. I do not have a financial interest in the other companies mentioned as of the time of writing. (but I’m happy to, call me)

Part 1: The Model

We’ll begin our tour with what model to use. In general, you want models that are a blend of cost efficient with effective performance. One of my favorite sites for this is Artificial Analysis; there’s a nice little grid on their models page that shows cost versus intelligence. What we’re looking for in this grid is models that are at the top left corner - the vertical (y) axis is brains, where higher is better, and the horizontal (x) axis is cost, where to the left is lower.

The current winner here is DeepSeek V4 Flash 0731, which has a crazy low cost and lots of brains, on par with OpenAI’s newest model, GPT-5.6 Luna. On the far right is Claude Opus 5, which has about 15% more brains but 40x the cost. The worst quadrant to be in is the lower right - high cost, low brains.

For the purposes of building the cheapest agentic system, DeepSeek is going to be your daily driver model.

Now, it’s worth pointing out, as I have in my book Almost Timeless: 48 Foundation Principles of Generative AI that a daily driver may not be the smartest model, but in terms of day to day work, a model like DeepSeek v4 Flash is going to get the job done most of the time. Here’s a bit of retrospective, by the way, putting DeepSeek on the same scale as all of OpenAI’s major models over the years to see where it stacks up in terms of brains.

DeepSeek V4 Flash outcompetes all but the most recent releases of OpenAI’s models over the years; it is almost 50% smarter than last summer’s flagship model, GPT-5, and is only 17% less capable than OpenAI’s current flagship model.

Here’s the same chart from the Claude world:

DeepSeek V4 Flash is about on parity with Claude Opus 4.7 - which came out in April 2026, a scant FOUR MONTHS AGO.

Now, times change, tech changes, and what you should be doing is checking in on these kinds of charts over time to see which model is closest to that top left corner. This month, it’s DeepSeek V4 Flash. Next month, it might be completely different. It’s our responsibility to keep up with the charts and use the cheapest, best brains we can get a hold of.

Now that we know what model we’re aiming to use, we have to figure out where to use it.

Part 2: The Host

Just like web hosting companies host websites, model hosting companies - called inference providers - host models. There are so, so many of these out there, and they compete mainly on two things, speed and price. Some providers charge a premium but generate results (tokens per second) at ridiculous speeds, like Cerebras. Others offer a wide variety of models at slower speeds but are cheap (like DeepInfra).

Choosing a provider is straightforward: because you’ve decided the model already, it’s a question of pricing and availability. In Google AI Mode, modify this prompt to suit your needs:

Help me create a list of inference providers that match these criteria. First and most important, they MUST offer this exact model: {model}. This is immutable and non-negotiable; a provider that does not offer this model does not make the list. Second, identify the pricing for this model in three categories: cost per input tokens, cost per output tokens, cost per cached tokens. If a provider does not offer pricing for this model for cached tokens, disqualify them. Third, the provider MUST be a zero data retention (ZDR) inference provider. If ZDR pricing is additional, compute it as part of the token costs. ZDR capability is mandatory; if a provider does not offer ZDR, disqualify them. Fourth, if available, obtain the tokens per second for this model for each provider. Return your results as an ordered list in ascending order by lowest cost per tokens for each provider for our chosen model.

You might want to add specific additional needs like SOC 2 compliance, GDPR compliance, etc. To the prompt based on your needs, so customize it any way you like.

With any model you choose, be sure you capture the full model name; DeepSeek v4 Flash for example has an antecedent that lacks the 0731 suffix. Our exact model that we want is DeepSeek v4 Flash 0731.

When I stick this into Google, DeepInfra, Fireworks AI, and OpenCode Zen show up as good options. Which one you choose will be based on how much you prioritize speed versus cost. If you told me to pick one and only one, I’ve been a customer of DeepInfra for a couple of years now and have no complaints at all, BUT there is also a case to be made for OpenCode Zen. More on that in a minute.

What I like, for Leslie’s specific use case, is that pay as you go providers mean that you’re not paying if you’re not using the AI AND there’s a strong economic incentive for you to use AI as little as possible and be as efficient in its use as possible. One of the problems with token plans (which include things like Claude Pro/Max, etc.) is that if you haven’t hit your weekly/monthly limits, you’re wasting money - and thus you’re more likely to use AI frivolously. With pay as you go, you only pay for what you use.

Part 3: The Hardware

For a second computer setup that’s cheap, we have to think about how computers work. The graphical user interface we’re all used to on Windows or Mac or even desktop Linux, as well as on our phones and tablets, is an INCREDIBLY inefficient waste of compute resources. It takes enormous amounts of memory and processing power to draw and maintain the interface compared to pure text-based interfaces.

Now, the crusty old GenX computer nerd in me says that everyone should know how to use a text-based interface (often called a command line or command prompt or terminal), but that’s not realistic. However, there is one user that LOVES text-based interfaces.

Yup, you guessed it. That’s AI. AI is far, far more efficient at typing than it is using a mouse, so for our second computer as Leslie asked about, we’re going to aim for a super cheap box that can run a terminal, store things, and run an AI harness. At a price point of roughly USD 500, you won’t be running AI models directly on this hardware (hence why we searched for hosting providers in Part 2), but you’ll have a decent machine with good storage.

On the shopping venue of your choice, look for what are called gaming mini-PCs. These typically will have AMD Ryzen chips, a small hard drive (typically 256 GB or 512 GB SSD), and between 16 GB and 32 GB of RAM. The cardinal rule of computing is that you want as much RAM/memory as money can buy; a slightly slower processor with more RAM is better than a fast processor with not enough RAM. RAM is like highway lanes; a Bugatti stuck in traffic on a single lane dirt road will not go as fast as a Prius on an 8 lane highway with no traffic jam.

Google AI Mode is handy here as well. Modify this prompt to suit your needs, especially if there are some companies you would prefer not to do business with:

Help me create a list of vendors that offer gaming mini PCs for sale that ship to my location: {locale}. My criteria are that the machine cost less than {amount} inclusive of shipping and that it have a minimum of 16 GB of RAM and 500 GB of disk space, ideally with an SSD. 32 GB of RAM is preferred, and more disk space is always preferred. The system MUST be able to run Ubuntu Linux 26.06 in headless mode. The CPU can be any make or model that offers a base clock speed of 3 GHz; AMD, Intel, or other vendors are fine as long as they are fully supported on Ubuntu. Ethernet and Wifi are mandatory. USB-C, Bluetooth, and HDMI are preferred. eGPU support is preferred. The following vendors and resellers are preferred: {preferred list}. The following vendors and resellers are forbidden: {banned list} The use case for this device will be to run OpenCode and Ubuntu Linux, plus apps like PostgreSQL, Docker, SQLite, Apache2, and similar server-like systems for a single person. Arrange your results in ascending order by price as an ordered list.

I spotted some random Chinese computer on Amazon that was selling for USD 499 with 32 GB of RAM and a 1 TB SSD (affiliate link!) that has a name that resembles what happens if you stuff Scrabble tiles in your mouth and then spit them out on the table. It’s got a 2023 chip in it, the AMD Ryzen 7730U, which is plenty fast for what we’re doing.

Why these specs? You want the extra RAM and disk space so you can run multiple local applications together on the same box. For example, if you want to run Hermes Agent, chances are you’ll want it in something like a Docker container, and the RAM/disk space will REALLY help with that. Likewise, if you want to roll your own local apps, you’ll probably be running a server that has a database, maybe even a local webserver, and more memory and disk space will really help there.

And technically, though it’s a miserable experience, a mini PC like this CAN do local inference with small models. Using something like llama.cpp, koboldcpp, or Unsloth Studio, you COULD theoretically serve up a small model like Gemma 4 E4B and get a modest little AI server running that can do basic things like summarization.

Once you get your hardware, you’ll want to erase the operating system on it and install a version of Linux. Linux is the best choice for this kind of computer because it can run using very few system resources. I’d suggest Ubuntu Linux in LTS flavor - LTS stands for Long Term Support, and the Ubuntu Foundation warrants that a version of Ubuntu will be supported for 10 years from the launch date. The current version is 26.04 LTS, Resolute Raccoon.

One thing that’s nice about Ubuntu Linux is that you can start it up with a GUI for configuration and all the comforts of modern computing, and then once everything is all square, you can shut down the GUI to free up resources, running it in text-based interface alone.

Part 4: The Harness

AI models by themselves are smart but are prone to things like hallucinations. Model hosts can add some guardrails and some tuning, but the real magic happens when you put a good model in a great harness. Think of the model like the engine of a car. An engine isn’t much good by itself, and a car without an engine is a lawn ornament, doubly so if it’s on cinderblocks.

But a good engine in a great car? That’s where, quite literally, the rubber meets the road. And as with cars, sometimes you can do with a good engine but not a great one if the rest of the car is nice. Unless you’re driving NASCAR or Formula 1, a Prius doesn’t need a V8 engine.

Harnesses are the interfaces to AI. When you use ChatGPT on the web, OpenAI has put a harness around its models, and what you experience as ChatGPT is their tuned harness. The same is true for Gemini, for Claude, etc. - and different harnesses do different things. Claude Code, for example, has hundreds of words of specific language built into its system prompts to behave a certain way, plus a slew of deterministic rules that silently reject bad outputs from the Claude models before you ever see them as a user.

For our purposes, because we’re trying to build a scrappy AI setup, we want a harness that’s free and supports multiple providers. For that, there’s no better harness than OpenCode. OpenCode is Free Open Source Software, and it comes in 2 flavors, a command line version and a GUI version. What’s really nice about it is that the GUI version is built on top of the command line version, so you don’t have to do anything differently and you can configure it in GUI mode, then use it later in command line mode with no changes at all.

OpenCode also supports all the modern skills and plugins that other AI systems use, so if you see a cool skill that someone’s showing off in Claude Code, for example, you can install that same skill in OpenCode.

OpenCode also offers 2 paid coding plans to go with it, OpenCode Zen which is pay as you go, and OpenCode Go, which is a subscription plan. There are some free models in OpenCode Zen but those DO collect your data and are not zero data retention. Remember in the world of AI that if you’re not paying, you and your data are the product being sold to someone else.

If you want the convenience of not having to manage your AI hosting separate from your AI harness, OpenCode Zen is a great choice. If you want the lowest possible costs, then use OpenCode with DeepInfra.

Part 5: Wrapping Up, the Process in a Nutshell

So in a nutshell, here is the order of operations to get up and running - and you can put this list (or this entire newsletter, really) into your favorite chat-based AI tool to walk you through this process.

1. Choose a model.

2. Choose a hosting provider.

3. Choose a hardware box of some kind.

4. Install Linux on that box.

5. Install OpenCode on that box.

6. Connect OpenCode to your hosting provider.

With those six big steps, you’re ready to go! I would suggest also installing and configuring tmux on your new box, because that gives you the ability to remote control it very easily, and if you want to get FANCY, install Tailscale on it as well, to create a VPN of your computers together so you can access your new AI box from anywhere in the world. That’s probably best for another time, though your AI of choice can walk you through that pretty easily.

The key to remember here is that this machine is a self-contained little server. Once you have OpenCode installed on it and connected to your model of choice, one of the first tasks you can do is put it to work securing itself. Using your favorite deep research tools, ask for a best practices guide to securing your little computer and optimizing it for AI usage, especially with the most popular command line tools that will help AI save tokens and usage. Because you’re using a provider like DeepInfra, every request you make costs you a tiny bit of money, and the more you can reduce that, the more you save.

If you deploy this system as written, you’ll spend about USD 500 on the hardware, and probably USD 5 to 10 per month in AI inference costs for moderate usage, which I define as a major coding project per week, something where your AI is working with sustained effort for about 2 hours a day. Models like DeepSeek V4 and similarly capable models are incredibly capable and dirt cheap to use.

It’s worth pointing out that if you have a working computer today, you could skip the hardware purchase and install OpenCode on your computer as is, eliminating the hardware cost. For folks on limited incomes, this is a great way to get access to high end AI without high end subscriptions, like job seekers without stable income.

Enjoy running your own little AI operations center!

Tyler Durden Tue, 08/11/2026 - 06:30

A third straight playoff-less season may force the Rangers to reconsider their retool.

The Minions are taking Hollywood by storm.

Brooklyn subtenant Kyle Harvey has gained 16 million views by filming his nightmare living situation with roommate Stephen Pulido.

Everything is on the table.