Take a look at The One, a Los Angeles estate with a whopping 105,000 square feet of living area.
The interiors of the 105,000-square-foot property, which sits on a five-acre parcel in the wealthy Los Angeles suburb of Bel Air and is suitably titled The One, have been a well guarded secret. We got an intimate look inside this world-record-breaking property, as well as the creative and aesthetic geniuses behind it.
The estate appears to float above the city, surrounded on three sides by a moat and a 400-foot-long running track. Completed over eight years—and requiring 600 workers to build—the home was designed by architect Paul McClean and interior designer Kathryn Rotondi, who were enlisted by owner and developer Nile Niami to help it live up to its standard.
"This endeavor seemed both exhilarating and daunting," McClean says. However, the home's remarkable location and McClean's long-standing relationship with Niami persuaded him to "build something unique and extraordinary" rather than just take on the job.
And McClean has more than delivered.
The home's main entrance leads to a variety of meeting places with magnificent 360-degree views of the Pacific Ocean, downtown Los Angeles, and the San Gabriel Mountains, thanks to its 26-foot-high ceilings. There is water at the entrance area, as well as a sculpture and a bridge. "We often employ water in our design approach because it provides a sensory change that helps you acclimatize to your environment," McClean explains.
Niami wanted a neutral palette that would enable the environment and vistas to shine, so she used black, white, and gray throughout the house.
McClean has combined the home's inside with outside "to create that quintessential L.A. lifestyle but on a larger scale," he says, drawing influence from the local environment and history of Los Angeles modernism. "We separated the entertaining spaces from the living portions to make the house feel more livable. The former are on the lowest level, which serves as a plinth for the rest of the house and minimizes its apparent mass."
The home's statistics, in addition to its eye-catching style, are equally impressive. There are 42 bathrooms, 21 bedrooms, a 5,500-square-foot master suite, a 30-car garage gallery with two car-display turntables, a four-lane bowling alley, a spa level, a 30-seat movie theater, a "philanthropy wing (with a capacity of 200) for charity galas, a 10,000-square-foot sky deck, and five swimming pools.
Rotondi, the creator of KFR Design, collaborated with Niami on the interior design to create different spaces that flow into one another despite the house's grandeur. "I was especially driven to 'wow factor' components in the hospitality business," Rotondi says, citing top luxury hotel brands such as Aman, Bulgari, and Baccarat as sources of inspiration. Meanwhile, the home's color scheme, soft textures, and lighting are a nod to Niami and McClean's favorite Tom Ford boutique on Rodeo Drive.
The house boasts an extraordinary collection of art, including a butterfly work by Stephen Wilson on the lower level and a Niclas Castello bespoke panel in black and silver in the office, thanks to a cooperation between Creative Art Partners and Art Angels. There is also a sizable collection of bespoke furniture pieces from byShowroom.
A house of this size will never be erected again in Los Angeles, thanks to recently enacted city rules, so The One will truly be one of a kind. "For all of us, this project has been such a long and instructive trip," McClean says. "It was exciting to develop and approached with excitement, but I don't think any of us knew how much effort and time it would take to finish the project."
More on Lifestyle
Tech With Dom
2 years ago
6 Awesome Desk Accessories You Must Have!
I'm gadget-obsessed. So I shared my top 6 desk gadgets.
These gadgets improve my workflow and are handy for working from home.
Without further ado...
Computer light bar Xiaomi Mi
I've previously recommended the Xiaomi Mi Light Bar, and I still do. It's stylish and convenient.
The Mi bar is a monitor-mounted desk lamp. The lamp's hue and brightness can be changed with a stylish wireless remote.
Changeable hue and brightness make it ideal for late-night work.
Desk Mat 2.
I wasn't planning to include a desk surface in this article, but I find it improves computer use.
The mouse feels smoother and is a better palm rest than wood or glass.
I'm currently using the overkill Razer Goliathus Extended Chroma RGB Gaming Surface, but I like RGB.
Using a desk surface or mat makes computer use more comfortable, and it's not expensive.
Third, the Logitech MX Master 3 Mouse
The Logitech MX Master 3 or any from the MX Master series is my favorite mouse.
The side scroll wheel on these mice is a feature I've never seen on another mouse.
Side scroll wheels are great for spreadsheets and video editing. It would be hard for me to switch from my Logitech MX Master 3 to another mouse. Only gaming is off-limits.
Google Nest 4.
Without a smart assistant, my desk is useless. I'm currently using the second-generation Google Nest Hub, but I've also used the Amazon Echo Dot, Echo Spot, and Apple HomePod Mini.
As a Pixel 6 Pro user, the Nest Hub works best with my phone.
My Nest Hub plays news, music, and calendar events. It also lets me control lights and switches with my smartphone. It plays YouTube videos.
Google Pixel Stand, No. 5
A wireless charger on my desk is convenient for charging my phone and other devices while I work. My desk has two wireless chargers. I have a Satechi aluminum fast charger and a second-generation Google Pixel Stand.
If I need to charge my phone and earbuds simultaneously, I use two wireless chargers. Satechi chargers are well-made and fast. Micro-USB is my only complaint.
The Pixel Stand converts compatible devices into a smart display for adjusting charging speeds and controlling other smart devices. My Pixel 6 Pro charges quickly. Here's my video review.
6. Anker Power Bank
Anker's 65W charger is my final recommendation. This online find was a must-have. This can charge my laptop and several non-wireless devices, perfect for any techie!
The charger has two USB-A ports and two USB-C ports, one with 45W and the other with 20W, so it can charge my iPad Pro and Pixel 6 Pro simultaneously.
Summary
These are some of my favorite office gadgets. My kit page has an updated list.
Links to the products mentioned in this article are in the appropriate sections. These are affiliate links.
You're up! Share the one desk gadget you can't live without and why.
Josh Chesler
3 years ago
10 Sneaker Terms Every Beginner Should Know
So you want to get into sneakers? Buying a few sneakers and figuring it out seems simple. Then you miss out on the weekend's instant-sellout releases, so you head to eBay, Twitter, or your local sneaker group to see what's available, since you're probably not ready to pay Flight Club prices just yet.
That's when you're bombarded with new nicknames, abbreviations, and general sneaker slang. It would take months to explain every word and sneaker, so here's a starter kit of ten simple terms to get you started. (Yeah, mostly Jordan. Does anyone really start with Kith or Nike SB?)
10. Colorways
Colorways are a common term in fashion, design, and other visual fields. It's just the product's color scheme. In the case of sneakers, the colorway is often as important as the actual model. Are this year's "Chicago" Air Jordan 1s more durable than last year's "Black/Gum" colorway? Because of their colorway and rarity, the Chicagos are worth roughly three pairs of the Black/Gum kicks.
Pro Tip: A colorway with a well-known nickname is almost always worth more than one without, and the same goes for collaborations.
9. Beaters
A “beater” is a well-worn, likely older model of shoe that has significant wear and tear on it. Rarely sold with the original box or extra laces, beaters rarely sell for much. Unlike most “worn” sneakers, beaters are used for rainy days and the gym. It's exactly what it sounds like, a box full of beaters, and they're a good place to start if you're looking for some cheap old kicks.
Pro Tip: Know which shoes clean up nicely. The shape of lower top sneakers with wider profiles, like SB Dunk Lows and Air Jordan 3s, tends to hold better over time than their higher and narrower cousins.
8. Retro
In the world of Jordan Brand, a “Retro” release is simply a release (or re-release) of a colorway after the shoe model's initial release. For example, the original Air Jordan 7 was released in 1992, but the Bordeaux colorway was re-released in 2011 and recently (2015). An Air Jordan model is released every year, and while half of them are unpopular and unlikely to be Retroed soon, any of them could be re-released whenever Nike and Jordan felt like it.
Pro Tip: Now that the Air Jordan line has been around for so long, the model that tends to be heavily retroed in a year is whichever shoe came out 23 (Michael Jordan’s number during the prime of his career) years ago. The Air Jordan 6 (1991) got new colorways last year, the Air Jordan 7 this year, and more Air Jordan 8s will be released later this year and early next year (1993).
7. PP/Inv
In spite of the fact that eBay takes roughly 10% of the final price, many sneaker buyers and sellers prefer to work directly with PayPal. Selling sneakers for $100 via PayPal invoice or $100 via PayPal friends/family is common on social media. Because no one wants their eBay account suspended for promoting PayPal deals, many eBay sellers will simply state “Message me for a better price.”
Pro Tip: PayPal invoices protect buyers well, but gifting or using Google Wallet does not. Unless you're certain the seller is legitimate, only use invoiced goods/services payments.
6. Yeezy
Kanye West and his sneakers are known as Yeezys. The rapper's first two Yeezys were made by Nike before switching to Adidas. Everything Yeezy-related will be significantly more expensive (and therefore have significantly more fakes made). Not only is the Nike Air Yeezy 2 “Red October” one of the most sought-after sneakers, but the Yeezy influence can be seen everywhere.
Pro Tip: If you're going to buy Yeezys, make sure you buy them from a reputable retailer or reseller. With so many fakes out there, it's not worth spending a grand on something you're not 100% sure is real.
5. GR/Limited
Regardless of how visually repulsive, uncomfortable, and/or impractical a sneaker is, if it’s rare enough, people will still want it. GR stands for General Release, which means they're usually available at retail. Reselling a “Limited Edition” release is costly. Supply and demand, but in this case, the limited supply drives up demand. If you want to get some of the colorways made for rappers, NBA players (Player Exclusive or PE models), and other celebrities, be prepared to pay a premium.
Pro Tip: Limited edition sneakers, like the annual Doernbecher Freestyle sneakers Nike creates with kids from Portland's Doernbecher Children's Hospital, will always be more expensive and limited. Or, you can use automated sneaker-buying software.
4. Grails
A “grail” is a pair of sneakers that someone desires above all others. To obtain their personal grails, people are willing to pay significantly more than the retail price. There doesn't have to be any rhyme or reason why someone chose a specific pair as their grails.
Pro Tip: For those who don't have them, the OG "Bred" or "Royal" Air Jordan 1s, the "Concord" Air Jordan 11s, etc., are all grails.
3. Bred
Anything released in “Bred” (black and red) will sell out quickly. Most resale Air Jordans (and other sneakers) come in the Bred colorway, which is a fan favorite. Bred is a good choice for a first colorway, especially on a solid sneaker silhouette.
Pro Tip: Apart from satisfying the world's hypebeasts, Bred sneakers will probably match a lot of your closet.
2. DS
DS = Deadstock = New. That's it. If something has been worn or tried on, it is no longer DS. Very Near Deadstock (VNDS) Pass As Deadstock It's a cute way of saying your sneakers have been worn but are still in good shape. In the sneaker world, “worn” means they are no longer new, but not too old or beat up.
Pro Tip: Ask for photos of any marks or defects to see what you’re getting before you buy used shoes, also find out if they come with the original box and extra laces, because that can be a sign that they’re in better shape.
1. Fake/Unauthorized
The words “Unauthorized,” “Replica,” “B-grades,” and “Super Perfect” all mean the shoes are fake. It means they aren't made by the actual company, no matter how close or how good the quality. If that's what you want, go ahead and get them. Do not wear them if you do not want the rest of the sneaker world to mock them.
Pro Tip: If you’re not sure if shoes are real or not, do a “Legit Check” on Twitter or Facebook. You'll get dozens of responses in no time.
Michael Le
3 years ago
Union LA x Air Jordan 2 “Future Is Now” PREVIEW
With the help of Virgil Abloh and Union LA‘s Chris Gibbs, it's now clear that Jordan Brand intended to bring the Air Jordan 2 back in 2022.
The “Future Is Now” collection includes two colorways of MJ's second signature as well as an extensive range of apparel and accessories.
“We wanted to juxtapose what some futuristic gear might look like after being worn and patina'd,”
Union stated on the collaboration's landing page.
“You often see people's future visions that are crisp and sterile. We thought it would be cool to wear it in and make it organic...”
The classic co-branding appears on short-sleeve tees, hoodies, and sweat shorts/sweat pants, all lightly distressed at the hems and seams.
Also, a filtered black-and-white photo of MJ graces the adjacent long sleeves, labels stitch into the socks, and the Jumpman logo adorns the four caps.
Liner jackets and flight pants will also be available, adding reimagined militaria to a civilian ensemble.
The Union LA x Air Jordan 2 (Grey Fog and Rattan) shares many of the same beats. Vintage suedes show age, while perforations and detailing reimagine Bruce Kilgore's design for the future.
The “UN/LA” tag across the modified eye stays, the leather patch across the tongue, and the label that wraps over the lateral side of the collar complete the look.
The footwear will also include a Crater Slide in the “Grey Fog” color scheme.
BUYING
On 4/9 and 4/10 from 9am-3pm, Union LA will be giving away a pair of Air Jordan 2s at their La Brea storefront (110 S. LA BREA AVE. LA, CA 90036). The raffle is only open to LA County residents with a valid CA ID. You must enter by 11:59pm on 4/10 to win. Winners will be notified via email.
You might also like
Dmitrii Eliuseev
2 years ago
Creating Images on Your Local PC Using Stable Diffusion AI
Deep learning-based generative art is being researched. As usual, self-learning is better. Some models, like OpenAI's DALL-E 2, require registration and can only be used online, but others can be used locally, which is usually more enjoyable for curious users. I'll demonstrate the Stable Diffusion model's operation on a standard PC.
Let’s get started.
What It Does
Stable Diffusion uses numerous components:
A generative model trained to produce images is called a diffusion model. The model is incrementally improving the starting data, which is only random noise. The model has an image, and while it is being trained, the reversed process is being used to add noise to the image. Being able to reverse this procedure and create images from noise is where the true magic is (more details and samples can be found in the paper).
An internal compressed representation of a latent diffusion model, which may be altered to produce the desired images, is used (more details can be found in the paper). The capacity to fine-tune the generation process is essential because producing pictures at random is not very attractive (as we can see, for instance, in Generative Adversarial Networks).
A neural network model called CLIP (Contrastive Language-Image Pre-training) is used to translate natural language prompts into vector representations. This model, which was trained on 400,000,000 image-text pairs, enables the transformation of a text prompt into a latent space for the diffusion model in the scenario of stable diffusion (more details in that paper).
This figure shows all data flow:
The weights file size for Stable Diffusion model v1 is 4 GB and v2 is 5 GB, making the model quite huge. The v1 model was trained on 256x256 and 512x512 LAION-5B pictures on a 4,000 GPU cluster using over 150.000 NVIDIA A100 GPU hours. The open-source pre-trained model is helpful for us. And we will.
Install
Before utilizing the Python sources for Stable Diffusion v1 on GitHub, we must install Miniconda (assuming Git and Python are already installed):
wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-Linux-x86_64.sh
chmod +x Miniconda3-py39_4.12.0-Linux-x86_64.sh
./Miniconda3-py39_4.12.0-Linux-x86_64.sh
conda update -n base -c defaults condaInstall the source and prepare the environment:
git clone https://github.com/CompVis/stable-diffusion
cd stable-diffusion
conda env create -f environment.yaml
conda activate ldm
pip3 install transformers --upgradeDownload the pre-trained model weights next. HiggingFace has the newest checkpoint sd-v14.ckpt (a download is free but registration is required). Put the file in the project folder and have fun:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Almost. The installation is complete for happy users of current GPUs with 12 GB or more VRAM. RuntimeError: CUDA out of memory will occur otherwise. Two solutions exist.
Running the optimized version
Try optimizing first. After cloning the repository and enabling the environment (as previously), we can run the command:
python3 optimizedSD/optimized_txt2img.py --prompt "hello world" --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1Stable Diffusion worked on my visual card with 8 GB RAM (alas, I did not behave well enough to get NVIDIA A100 for Christmas, so 8 GB GPU is the maximum I have;).
Running Stable Diffusion without GPU
If the GPU does not have enough RAM or is not CUDA-compatible, running the code on a CPU will be 20x slower but better than nothing. This unauthorized CPU-only branch from GitHub is easiest to obtain. We may easily edit the source code to use the latest version. It's strange that a pull request for that was made six months ago and still hasn't been approved, as the changes are simple. Readers can finish in 5 minutes:
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available at line 20 of ldm/models/diffusion/ddim.py ().
Replace if attr.device!= torch.device(cuda) with if attr.device!= torch.device(cuda) and torch.cuda.is available in line 20 of ldm/models/diffusion/plms.py ().
Replace device=cuda in lines 38, 55, 83, and 142 of ldm/modules/encoders/modules.py with device=cuda if torch.cuda.is available(), otherwise cpu.
Replace model.cuda() in scripts/txt2img.py line 28 and scripts/img2img.py line 43 with if torch.cuda.is available(): model.cuda ().
Run the script again.
Testing
Test the model. Text-to-image is the first choice. Test the command line example again:
python3 scripts/txt2img.py --prompt "hello world" --plms --ckpt sd-v1-4.ckpt --skip_grid --n_samples 1The slow generation takes 10 seconds on a GPU and 10 minutes on a CPU. Final image:
Hello world is dull and abstract. Try a brush-wielding hamster. Why? Because we can, and it's not as insane as Napoleon's cat. Another image:
Generating an image from a text prompt and another image is interesting. I made this picture in two minutes using the image editor (sorry, drawing wasn't my strong suit):
I can create an image from this drawing:
python3 scripts/img2img.py --prompt "A bird is sitting on a tree branch" --ckpt sd-v1-4.ckpt --init-img bird.png --strength 0.8It was far better than my initial drawing:
I hope readers understand and experiment.
Stable Diffusion UI
Developers love the command line, but regular users may struggle. Stable Diffusion UI projects simplify image generation and installation. Simple usage:
Unpack the ZIP after downloading it from https://github.com/cmdr2/stable-diffusion-ui/releases. Linux and Windows are compatible with Stable Diffusion UI (sorry for Mac users, but those machines are not well-suitable for heavy machine learning tasks anyway;).
Start the script.
Done. The web browser UI makes configuring various Stable Diffusion features (upscaling, filtering, etc.) easy:
V2.1 of Stable Diffusion
I noticed the notification about releasing version 2.1 while writing this essay, and it was intriguing to test it. First, compare version 2 to version 1:
alternative text encoding. The Contrastive LanguageImage Pre-training (CLIP) deep learning model, which was trained on a significant number of text-image pairs, is used in Stable Diffusion 1. The open-source CLIP implementation used in Stable Diffusion 2 is called OpenCLIP. It is difficult to determine whether there have been any technical advancements or if legal concerns were the main focus. However, because the training datasets for the two text encoders were different, the output results from V1 and V2 will differ for the identical text prompts.
a new depth model that may be used to the output of image-to-image generation.
a revolutionary upscaling technique that can quadruple the resolution of an image.
Generally higher resolution Stable Diffusion 2 has the ability to produce both 512x512 and 768x768 pictures.
The Hugging Face website offers a free online demo of Stable Diffusion 2.1 for code testing. The process is the same as for version 1.4. Download a fresh version and activate the environment:
conda deactivate
conda env remove -n ldm # Use this if version 1 was previously installed
git clone https://github.com/Stability-AI/stablediffusion
cd stablediffusion
conda env create -f environment.yaml
conda activate ldmHugging Face offers a new weights ckpt file.
The Out of memory error prevented me from running this version on my 8 GB GPU. Version 2.1 fails on CPUs with the slow conv2d cpu not implemented for Half error (according to this GitHub issue, the CPU support for this algorithm and data type will not be added). The model can be modified from half to full precision (float16 instead of float32), however it doesn't make sense since v1 runs up to 10 minutes on the CPU and v2.1 should be much slower. The online demo results are visible. The same hamster painting with a brush prompt yielded this result:
It looks different from v1, but it functions and has a higher resolution.
The superresolution.py script can run the 4x Stable Diffusion upscaler locally (the x4-upscaler-ema.ckpt weights file should be in the same folder):
python3 scripts/gradio/superresolution.py configs/stable-diffusion/x4-upscaling.yaml x4-upscaler-ema.ckptThis code allows the web browser UI to select the image to upscale:
The copy-paste strategy may explain why the upscaler needs a text prompt (and the Hugging Face code snippet does not have any text input as well). I got a GPU out of memory error again, although CUDA can be disabled like v1. However, processing an image for more than two hours is unlikely:
Stable Diffusion Limitations
When we use the model, it's fun to see what it can and can't do. Generative models produce abstract visuals but not photorealistic ones. This fundamentally limits The generative neural network was trained on text and image pairs, but humans have a lot of background knowledge about the world. The neural network model knows nothing. If someone asks me to draw a Chinese text, I can draw something that looks like Chinese but is actually gibberish because I never learnt it. Generative AI does too! Humans can learn new languages, but the Stable Diffusion AI model includes only language and image decoder brain components. For instance, the Stable Diffusion model will pull NO WAR banner-bearers like this:
V1:
V2.1:
The shot shows text, although the model never learned to read or write. The model's string tokenizer automatically converts letters to lowercase before generating the image, so typing NO WAR banner or no war banner is the same.
I can also ask the model to draw a gorgeous woman:
V1:
V2.1:
The first image is gorgeous but physically incorrect. A second one is better, although it has an Uncanny valley feel. BTW, v2 has a lifehack to add a negative prompt and define what we don't want on the image. Readers might try adding horrible anatomy to the gorgeous woman request.
If we ask for a cartoon attractive woman, the results are nice, but accuracy doesn't matter:
V1:
V2.1:
Another example: I ordered a model to sketch a mouse, which looks beautiful but has too many legs, ears, and fingers:
V1:
V2.1: improved but not perfect.
V1 produces a fun cartoon flying mouse if I want something more abstract:
I tried multiple times with V2.1 but only received this:
The image is OK, but the first version is closer to the request.
Stable Diffusion struggles to draw letters, fingers, etc. However, abstract images yield interesting outcomes. A rural landscape with a modern metropolis in the background turned out well:
V1:
V2.1:
Generative models help make paintings too (at least, abstract ones). I searched Google Image Search for modern art painting to see works by real artists, and this was the first image:
I typed "abstract oil painting of people dancing" and got this:
V1:
V2.1:
It's a different style, but I don't think the AI-generated graphics are worse than the human-drawn ones.
The AI model cannot think like humans. It thinks nothing. A stable diffusion model is a billion-parameter matrix trained on millions of text-image pairs. I input "robot is creating a picture with a pen" to create an image for this post. Humans understand requests immediately. I tried Stable Diffusion multiple times and got this:
This great artwork has a pen, robot, and sketch, however it was not asked. Maybe it was because the tokenizer deleted is and a words from a statement, but I tried other requests such robot painting picture with pen without success. It's harder to prompt a model than a person.
I hope Stable Diffusion's general effects are evident. Despite its limitations, it can produce beautiful photographs in some settings. Readers who want to use Stable Diffusion results should be warned. Source code examination demonstrates that Stable Diffusion images feature a concealed watermark (text StableDiffusionV1 and SDV2) encoded using the invisible-watermark Python package. It's not a secret, because the official Stable Diffusion repository's test watermark.py file contains a decoding snippet. The put watermark line in the txt2img.py source code can be removed if desired. I didn't discover this watermark on photographs made by the online Hugging Face demo. Maybe I did something incorrectly (but maybe they are just not using the txt2img script on their backend at all).
Conclusion
The Stable Diffusion model was fascinating. As I mentioned before, trying something yourself is always better than taking someone else's word, so I encourage readers to do the same (including this article as well;).
Is Generative AI a game-changer? My humble experience tells me:
I think that place has a lot of potential. For designers and artists, generative AI can be a truly useful and innovative tool. Unfortunately, it can also pose a threat to some of them since if users can enter a text field to obtain a picture or a website logo in a matter of clicks, why would they pay more to a different party? Is it possible right now? unquestionably not yet. Images still have a very poor quality and are erroneous in minute details. And after viewing the image of the stunning woman above, models and fashion photographers may also unwind because it is highly unlikely that AI will replace them in the upcoming years.
Today, generative AI is still in its infancy. Even 768x768 images are considered to be of a high resolution when using neural networks, which are computationally highly expensive. There isn't an AI model that can generate high-resolution photographs natively without upscaling or other methods, at least not as of the time this article was written, but it will happen eventually.
It is still a challenge to accurately represent knowledge in neural networks (information like how many legs a cat has or the year Napoleon was born). Consequently, AI models struggle to create photorealistic photos, at least where little details are important (on the other side, when I searched Google for modern art paintings, the results are often even worse;).
When compared to the carefully chosen images from official web pages or YouTube reviews, the average output quality of a Stable Diffusion generation process is actually less attractive because to its high degree of randomness. When using the same technique on their own, consumers will theoretically only view those images as 1% of the results.
Anyway, it's exciting to witness this area's advancement, especially because the project is open source. Google's Imagen and DALL-E 2 can also produce remarkable findings. It will be interesting to see how they progress.
Hunter Walk
2 years ago
Is it bad of me to want our portfolio companies to generate greater returns for outside investors than they did for us as venture capitalists?
Wishing for Lasting Companies, Not Penny Stocks or Goodwill Write-Downs
Get me a NASCAR-style company-logoed cremation urn (notice to the executor of my will, theres gonna be a lot of weird requests). I believe in working on projects that would be on your tombstone. As the Homebrew logo is tattooed on my shoulder, expanding the portfolio to my posthumous commemoration is easy. But this isn't an IRR victory lap; it's a hope that the firms we worked for would last beyond my lifetime.
![a little boy planting a dollar bill in the ground and pouring a watering can out on it, digital art [DALL-E]](https://storage.googleapis.com/int3grity/posts/V62hkReDx56S/images/vMwzqrYeXaYnUIMXAdTY9)
Venture investors too often take credit or distance themselves from startups based on circumstances. Successful companies tell stories of crucial introductions, strategy conversations, and other value. Defeats Even whether our term involves Board service or systematic ethical violations, I'm just a little investment, so there's not much I can do. Since I'm guilty, I'm tossing stones from within the glass home (although we try to own our decisions through the lifecycle).
Post-exit company trajectories are usually unconfounded. Off the cap table, no longer a shareholder (or a diminishing one as you sell off/distribute), eventually leaving the Board. You can cheer for the squad or forget about it, but you've freed the corporation and it's back to portfolio work.
As I look at the downward track of most SPACs and other tarnished IPOs from the last few years, I wonder how I would feel if those were my legacy. Is my job done? Yes. When investing in a business, the odds are against it surviving, let alone thriving and being able to find sunlight. SPAC sponsors, institutional buyers, retail investments. Free trade in an open market is their right. Risking and losing capital is the system working! But
We were lead or co-lead investors in our first three funds, but as additional VCs joined the company, we were pushed down the cap table. Voting your shares rarely matters; supporting the firm when they need it does. Being valuable, consistent, and helping the company improve builds trust with the founders.
I hope every startup we sponsor becomes a successful public company before, during, and after we benefit. My perspective of American capitalism. Well, a stock ticker has a lot of garbage, and I support all types of regulation simplification (in addition to being a person investor in the Long-Term Stock Exchange). Yet being owned by a large group of investors and making actual gains for them is great. Likewise does seeing someone you met when they were just starting out become a public company CEO without losing their voice, leadership, or beliefs.
I'm just thinking about what we can do from the start to realize value from our investments and build companies with bright futures. Maybe seed venture financing shouldn't impact those outcomes, but I'm not comfortable giving up that obligation.
Will Leitch
2 years ago
Don't treat Elon Musk like Trump.
He’s not the President. Stop treating him like one.
Elon Musk tweeted from Qatar, where he was watching the World Cup Final with Jared Kushner.
Musk's subsequent Tweets were as normal, basic, and bland as anyone's from a World Cup Final: It's depressing to see the world's richest man looking at his phone during a grand ceremony. Rich guy goes to rich guy event didn't seem important.
Before Musk posted his should-I-step-down-at-Twitter poll, CNN ran a long segment asking if it was hypocritical for him to reveal his real-time location after defending his (very dumb) suspension of several journalists for (supposedly) revealing his assassination coordinates by linking to a site that tracks Musks private jet. It was hard to ignore CNN's hypocrisy: It covered Musk as Twitter CEO like President Trump. EVERY TRUMP STORY WAS BASED ON HIM SAYING X, THEN DOING Y. Trump would do something horrific, lie about it, then pretend it was fine, then condemn a political rival who did the same thing, be called hypocritical, and so on. It lasted four years. Exhausting.
It made sense because Trump was the President of the United States. The press's main purpose is to relentlessly cover and question the president.
It's strange to say this out. Twitter isn't America. Elon Musk isn't a president. He maintains a money-losing social media service to harass and mock people he doesn't like. Treating Musk like Trump, as if he should be held accountable like Trump, shows a startling lack of perspective. Some journalists treat Twitter like a country.
The compulsive, desperate way many journalists utilize the site suggests as much. Twitter isn't the town square, despite popular belief. It's a place for obsessives to meet and converse. Journalists say they're breaking news. Their careers depend on it. They can argue it's a public service. Nope. It's a place lonely people go to speak all day. Twitter. So do journalists, Trump, and Musk. Acting as if it has a greater purpose, as if it's impossible to break news without it, or as if the republic is in peril is ludicrous. Only 23% of Americans are on Twitter, while 25% account for 97% of Tweets. I'd think a large portion of that 25% are journalists (or attention addicts) chatting to other journalists. Their loudness makes Twitter seem more important than it is. Nope. It's another stupid website. They were there before Twitter; they will be there after Twitter. It’s just a website. We can all get off it if we want. Most of us aren’t even on it in the first place.
Musk is a website-owner. No world leader. He's not as accountable as Trump was. Musk is cable news's primary character now that Trump isn't (at least for now). Becoming a TV news anchor isn't as significant as being president. Elon Musk isn't as important as we all pretend, and Twitter isn't even close. Twitter is a dumb website, Elon Musk is a rich guy going through a midlife crisis, and cable news is lazy because its leaders thought the entire world was on Twitter and are now freaking out that their playground is being disturbed.
I’ve said before that you need to leave Twitter, now. But even if you’re still on it, we need to stop pretending it matters more than it does. It’s a site for lonely attention addicts, from the man who runs it to the journalists who can’t let go of it. It’s not a town square. It’s not a country. It’s not even a successful website. Let’s stop pretending any of it’s real. It’s not.