The company's epidemic gains are gone.

Mark Zuckerberg was in line behind Jeff Bezos and Bill Gates less than two years ago. His wealth soared to $142 billion. Facebook's shares reached $382 in September 2021.

What comes next is either the start of something truly innovative or the beginning of an epic rise and fall story.

In order to start over (and avoid Facebook's PR issues), he renamed the firm Meta. Along with the new logo, he announced a turn into unexplored territory, the Metaverse, as the next chapter for the internet after mobile. Or, Zuckerberg believed Facebook's death was near, so he decided to build a bigger, better, cooler ship. Then we saw his vision (read: dystopian nightmare) in a polished demo that showed Zuckerberg in a luxury home and on a spaceship with aliens. Initially, it looked entertaining. A problem was obvious, though. He might claim this was the future and show us using the Metaverse for business, play, and more, but when I took off my headset, I'd realize none of it was genuine.

The stock price is almost as low as January 2019, when Facebook was dealing with the aftermath of the Cambridge Analytica crisis.

Irony surrounded the technology's aim. Zuckerberg says the Metaverse connects people. Despite some potential uses, this is another step away from physical touch with people. Metaverse worlds can cause melancholy, addiction, and mental illness. But forget all the cool stuff you can't afford. (It may be too expensive online, too.)

Metaverse activity slowed for a while. In early February 2022, we got an earnings call update. Not good. Reality Labs lost $10 billion on Oculus and Zuckerberg's Metaverse. Zuckerberg expects losses to rise. Meta's value dropped 20% in 11 minutes after markets closed.

It was a sign of things to come.

The corporation has failed to create interest in Metaverse, and there is evidence the public has lost interest. Meta still relies on Facebook's ad revenue machine, which is also struggling. In July, the company announced a decrease in revenue and missed practically all its forecasts, ending a decade of exceptional growth and relentless revenue. They blamed a dismal advertising demand climate, and Apple's monitoring changes smashed Meta's ad model. Throw in whistleblowers, leaked data revealing the firm knows Instagram negatively affects teens' mental health, the current Capital Hill probe, and the fact TikTok is eating its breakfast, lunch, and dinner, and 2022 might be the corporation's worst year ever.

After a rocky start, tech saw unprecedented growth during the pandemic. It was a tech bubble and then some.

The gains reversed after the dust settled and stock markets adjusted. Meta's year-to-date decline is 60%. Apple Inc is down 14%, Amazon is down 26%, and Alphabet Inc is down 29%. At the time of writing, Facebook's stock price is almost as low as January 2019, when the Cambridge Analytica scandal broke. Zuckerberg owns 350 million Meta shares. This drop costs him $71 billion.

The company's problems are growing, and solutions won't be easy.

• Facebook's period of unabated expansion and exorbitant ad revenue is ended, and the company's impact is dwindling as it continues to be the program that only your parents use. Because of the decreased ad spending and stagnant user growth, Zuckerberg will have less time to create his vision for the Metaverse because of the declining stock value and decreasing ad spending.

• Instagram is progressively dying in its attempt to resemble TikTok, alienating its user base and further driving users away from Meta-products.

• And now that the corporation has shifted its focus to the Metaverse, it is clear that, in its eagerness to improve its image, it fired the launch gun too early. You're fighting a lost battle when you announce an idea and then claim it won't happen for 10-15 years. When the idea is still years away from becoming a reality, the public is already starting to lose interest.

So, as I questioned earlier, is it the beginning of a technological revolution that will take this firm to stratospheric growth and success, or are we witnessing the end of Meta and Zuckerberg himself?

As technology develops, you should stay up to date

You don't want to fall behind, do you? This post covers 7 tech-related things you should know.

You'll learn how to operate your computer (and other electronic devices) like an expert and how to leverage the Internet and social media to create your brand and business. Read on to stay relevant in today's tech-driven environment.

You must learn how to code.

Future-language is coding. It's how we and computers talk. Learn coding to keep ahead.

Try Codecademy or Code School. There are also numerous free courses like Coursera or Udacity, but they take a long time and aren't necessarily self-paced, so it can be challenging to find the time.

Artificial intelligence (AI) will transform all jobs.

Our skillsets must adapt with technology. AI is a must-know topic. AI will revolutionize every employment due to advances in machine learning.

Here are seven AI subjects you must know.

What is artificial intelligence?

How does artificial intelligence work?

What are some examples of AI applications?

How can I use artificial intelligence in my day-to-day life?

What jobs have a high chance of being replaced by artificial intelligence and how can I prepare for this?

Can machines replace humans? What would happen if they did?

How can we manage the social impact of artificial intelligence and automation on human society and individual people?

Blockchain Is Changing the Future

Few of us know how Bitcoin and blockchain technology function or what impact they will have on our lives. Blockchain offers safe, transparent, tamper-proof transactions.

It may alter everything from business to voting. Seven must-know blockchain topics:

1. Describe blockchain.

2. How does the blockchain function?

3. What advantages does blockchain offer?

4. What possible uses for blockchain are there?

5. What are the dangers of blockchain technology?

6. What are my options for using blockchain technology?

7. What does blockchain technology's future hold?

Cryptocurrencies are here to stay

Cryptocurrencies employ cryptography to safeguard transactions and manage unit creation. Decentralized cryptocurrencies aren't controlled by governments or financial institutions.

Bitcoin, the first cryptocurrency, was launched in 2009. Cryptocurrencies can be bought and sold on decentralized exchanges.

Bitcoin is here to stay.

Bitcoin isn't a fad, despite what some say. Since 2009, Bitcoin's popularity has grown. Bitcoin is worth learning about now. Since 2009, Bitcoin has developed steadily.

With other cryptocurrencies emerging, many people are wondering if Bitcoin still has a bright future. Curiosity is natural. Millions of individuals hope their Bitcoin investments will pay off since they're popular now.

Thankfully, they will. Bitcoin is still running strong a decade after its birth. Here's why.

The Internet of Things (IoT) is no longer just a trendy term.

IoT consists of internet-connected physical items. These items can share data. IoT is young but developing fast.

20 billion IoT-connected devices are expected by 2023. So much data! All IT teams must keep up with quickly expanding technologies. Four must-know IoT topics:

1. Recognize the fundamentals: Priorities first! Before diving into more technical lingo, you should have a fundamental understanding of what an IoT system is. Before exploring how something works, it's crucial to understand what you're working with.

2. Recognize Security: Security does not stand still, even as technology advances at a dizzying pace. As IT professionals, it is our duty to be aware of the ways in which our systems are susceptible to intrusion and to ensure that the necessary precautions are taken to protect them.

3. Be able to discuss cloud computing: The cloud has seen various modifications over the past several years once again. The use of cloud computing is also continually changing. Knowing what kind of cloud computing your firm or clients utilize will enable you to make the appropriate recommendations.

4. Bring Your Own Device (BYOD)/Mobile Device Management (MDM) is a topic worth discussing (MDM). The ability of BYOD and MDM rules to lower expenses while boosting productivity among employees who use these services responsibly is a major factor in their continued growth in popularity.

IoT Security is key

As more gadgets connect, they must be secure. IoT security includes securing devices and encrypting data. Seven IoT security must-knows:

1. fundamental security ideas

2. Authorization and identification

3. Cryptography

4. electronic certificates

5. electronic signatures

6. Private key encryption

7. Public key encryption

Final Thoughts

With so much going on in the globe, it can be hard to stay up with technology. We've produced a list of seven tech must-knows.

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 conda

Install 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 --upgrade

Download 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 1

Almost. 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 1

Stable 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 1

The 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 0.8

It 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 ldm

Hugging 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.ckpt

This 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.

Elon Musk, Matt Taibbi, the 'Twitter Files,' and Hunter Biden's laptop: what gives?

Explaining Twitter Files

Matt Taibbi released "The Twitter Files," a batch of emails sent by Twitter executives discussing the company's decision to stop an October 2020 New York Post story online.

What's on Twitter? New York Post and Fox News call them "bombshell" documents. Or, as a Post columnist admitted, are they "not the smoking gun"? Onward!

What started this?

The New York Post published an exclusive, potentially explosive story in October 2020: Biden's Secret Emails: Ukrainian executive thanks Hunter Biden for'meeting' veep dad. The story purported to report the contents of a laptop brought to the tabloid by a Delaware computer repair shop owner who said it belonged to President Biden's second son, Hunter Biden. Emails and files on the laptop allegedly showed how Hunter peddled influence with Ukranian businessmen and included a "raunchy 12-minute video" of Hunter smoking crack and having sex.

Twitter banned links to the Post story after it was published, calling it "hacked material." The Post's Twitter account was suspended for multiple days.

Why? Yoel Roth, Twitter's former head of trust and safety, said the company couldn't verify the story, implying they didn't trust the Post.

Twitter's stated purpose rarely includes verifying news stories. This seemed like intentional political interference. This story was hard to verify because the people who claimed to have found the laptop wouldn't give it to other newspapers. (Much of the story, including Hunter's business dealings in Ukraine and China, was later confirmed.)

Roth: "It looked like a hack and leak."

So what are the “Twitter Files?”

Twitter's decision to bury the story became a political scandal, and new CEO Elon Musk promised an explanation. The Twitter Files, named after Facebook leaks.

Musk promised exclusive details of "what really happened" with Hunter Biden late Friday afternoon. The tweet was punctuated with a popcorn emoji.

Explaining Twitter Files

Three hours later, journalist Matt Taibbi tweeted more than three dozen tweets based on internal Twitter documents that revealed "a Frankensteinian tale of a human-built mechanism grown out of its designer's control."

Musk sees this release as a way to shape Twitter's public perception and internal culture in his image. We don't know if the CEO gave Taibbi the documents. Musk hyped the document dump before and during publication, but Taibbi cited "internal sources."

Taibbi shares email screenshots showing Twitter execs discussing the Post story and blocking its distribution. Taibbi says the emails show Twitter's "extraordinary steps" to bury the story.

Twitter communications chief Brandon Borrman has the most damning quote in the Files. Can we say this is policy? The story seemed unbelievable. It seemed like a hack... or not? Could Twitter, which ex-CEO Dick Costolo called "the free speech wing of the free speech party," censor a news story?

Many on the right say the Twitter Files prove the company acted at the behest of Democrats. Both parties had these tools, writes Taibbi. In 2020, both the Trump White House and Biden campaign made requests. He says the system for reporting tweets for deletion is unbalanced because Twitter employees' political donations favor Democrats. Perhaps. These donations may have helped Democrats connect with Twitter staff, but it's also possible they didn't. No emails in Taibbi's cache show these alleged illicit relations or any actions Twitter employees took as a result.

Even Musk's supporters were surprised by the drop. Miranda Devine of the New York Post told Tucker Carlson the documents weren't "the smoking gun we'd hoped for." Sebastian Gorka said on Truth Social, "So far, I'm deeply underwhelmed." DC Democrats collude with Palo Alto Democrats. Whoop!” The Washington Free Beacon's Joe Simonson said the Twitter files are "underwhelming." Twitter was staffed by Democrats who did their bidding. (Why?)

If "The Twitter Files" matter, why?

These emails led Twitter to suppress the Hunter Biden laptop story has real news value. It's rare for a large and valuable company like Twitter to address wrongdoing so thoroughly. Emails resemble FOIA documents. They describe internal drama at a company with government-level power. Katie Notopoulos tweeted, "Any news outlet would've loved this scoop!" It's not a'scandal' as teased."

Twitter's new owner calls it "the de facto public town square," implying public accountability. Like a government agency. Though it's exciting to receive once-hidden documents in response to a FOIA, they may be boring and tell you nothing new. Like Twitter files. We learned how Twitter blocked the Post's story, but not why. Before these documents were released, we knew Twitter had suppressed the story and who was involved.

These people were disciplined and left Twitter. Musk fired Vijaya Gadde, the former CLO who reportedly played a "key role" in the decision. Roth quit over Musk's "dictatorship." Musk arrived after Borrman left. Jack Dorsey, then-CEO, has left. Did those who digitally quarantined the Post's story favor Joe Biden and the Democrats? Republican Party opposition and Trump hatred? New York Post distaste? According to our documents, no. Was there political and press interference? True. We knew.

Taibbi interviewed anonymous ex-Twitter employees about the decision; all expressed shock and outrage. One source said, "Everyone knew this was fucked." Since Taibbi doesn't quote that expletive, we can assume the leaked emails contained few or no sensational quotes. These executives said little to support nefarious claims.

Outlets more invested in the Hunter Biden story than Gizmodo seem vexed by the release and muted headlines. The New York Post, which has never shied away from a blaring headline in its 221-year history, owns the story of Hunter Biden's laptop. Two Friday-night Post alerts about Musk's actions were restrained. Elon Musk will drop Twitter files on NY Post-Hunter Biden laptop censorship today. Elon Musk's Twitter dropped Post censorship details from Biden's laptop. Fox News' Apple News push alert read, "Elon Musk drops Twitter censorship documents."

Bombshell, bombshell, bombshell… what, exactly, is the bombshell? Maybe we've heard this story too much and are missing the big picture. Maybe these documents detail a well-documented decision.

The Post explains why on its website. "Hunter Biden laptop bombshell: Twitter invented reason to censor Post's reporting," its headline says.

Twitter's ad hoc decision to moderate a tabloid's content is not surprising. The social network had done this for years as it battled toxic users—violent white nationalists, virulent transphobes, harassers and bullies of all political stripes, etc. No matter how much Musk crows, the company never had content moderation under control. Buzzfeed's 2016 investigation showed how Twitter has struggled with abusive posters since 2006. Jack Dorsey and his executives improvised, like Musk.

Did the US government interfere with the ex-social VP's media company? That's shocking, a bombshell. Musk said Friday, "Twitter suppressing free speech by itself is not a 1st amendment violation, but acting under government orders with no judicial review is." Indeed! Taibbi believed this. August 2022: "The laptop is secondary." Zeynep Tufecki, a Columbia professor and New York Times columnist, says the FBI is cutting true story distribution. Taibbi retracted the claim Friday night: "I've seen no evidence of government involvement in the laptop story."

What’s the bottom line?

I'm still not sure what's at stake in the Hunter Biden scandal after dozens of New York Post articles, hundreds of hours of Fox News airtime, and thousands of tweets. Briefly: Joe Biden's son left his laptop with a questionable repairman. FBI confiscated it? The repairman made a copy and gave it to Rudy Giuliani's lawyer. The Post got it from Steve Bannon. On that laptop were videos of Hunter Biden smoking crack, cavorting with prostitutes, and emails about introducing his father to a Ukrainian businessman for $50,000 a month. Joe Biden urged Ukraine to fire a prosecutor investigating the company. What? The story seems to be about Biden family business dealings, right?

The discussion has moved past that point anyway. Now, the story is the censorship of it. Adrienne Rich wrote in "Diving Into the Wreck" that she came for "the wreck and not the story of the wreck" No matter how far we go, Hunter Biden's laptop is done. Now, the crash's story matters.

I'm dizzy. Katherine Miller of BuzzFeed wrote, "I know who I believe, and you probably do, too. To believe one is to disbelieve the other, which implicates us in the decision; we're stuck." I'm stuck. Hunter Biden's laptop is a political fabrication. You choose. I've decided.

This could change. Twitter Files drama continues. Taibbi said, "Much more to come." I'm dizzy.

Skip this if you don't want to discover why your lively, no-brainer pitch isn't making $10k a month.

You don't want to be repulsive as an entrepreneur or anyone else. Making friends, influencing people, and converting strangers into customers will be difficult if your words evoke disgust, distrust, or disrespect. You may be one of many entrepreneurs who do this obliviously and involuntarily.

I've had to master selling my skills to recruiters (to land 6-figure jobs on Wall Street), selling companies to buyers in M&A transactions, and selling my own companies' products to strangers-turned-customers. I probably committed every cardinal sin of sales repulsion before realizing it was me or my poor salesmanship strategy.

If you're launching a new business, frustrated by low conversion rates, or just curious if you're repelling customers, read on to identify (and avoid) the 6 fatal errors that can kill any sales pitch.

1. The first indication

So many people fumble before they even speak because they assume their role is to convince the buyer. In other words, they expect to pressure, arm-twist, and combat objections until they convert the buyer. Actuality, the approach stinks of disgust, and emotionally-aware buyers would feel "gross" immediately.

Instead of trying to persuade a customer to buy, ask questions that will lead them to do so on their own. When a customer discovers your product or service on their own, they need less outside persuasion. Why not position your offer in a way that leads customers to sell themselves on it?

2. A flawless performance

Are you memorizing a sales script, tweaking video testimonials, and expunging historical blemishes before hitting "publish" on your new campaign? If so, you may be hurting your conversion rate.

Perfection may be a step too far and cause prospects to mistrust your sincerity. Become a great conversationalist to boost your sales. Seriously. Being charismatic is hard without being genuine and showing a little vulnerability.

People like vulnerability, even if it dents your perfect facade. Show the customer's stuttering testimonial. Open up about your or your company's past mistakes (and how you've since improved). Make your sales pitch a two-way conversation. Let the customer talk about themselves to build rapport. Real people sell, not canned scripts and movie-trailer testimonials.

If marketing or sales calls feel like a performance, you may be doing something wrong or leaving money on the table.

3. Your greatest phobia

Three minutes into prospect talks, I'd start sweating. I was talking 100 miles per hour, covering as many bases as possible to avoid the ones I feared. I knew my then-offering was inadequate and my firm had fears I hadn't addressed. So I word-vomited facts, features, and everything else to avoid the customer's concerns.

Do my prospects know I'm insecure? Maybe not, but it added an unnecessary and unhelpful layer of paranoia that kept me stressed, rushed, and on edge instead of connecting with the prospect. Skirting around a company, product, or service's flaws or objections is a poor, temporary, lazy (and cowardly) decision.

How can you project confidence and trust if you're afraid? Before you make another sales call, face your shortcomings, weak points, and objections. Your company won't be everyone's cup of tea, but you should have answers to every question or objection. You should be your business's top spokesperson and defender.

4. The unintentional apologies

Have you ever begged for a sale? I'm going to say no, however you may be unknowingly emitting sorry, inferior, insecure energy.

Young founders, first-time entrepreneurs, and those with severe imposter syndrome may elevate their target customer. This is common when trying to get first customers for obvious reasons.

• Since you're truly new at this, you naturally lack experience.

• You don't have the self-confidence boost of thousands or hundreds of closed deals or satisfied client results to remind you that your good or service is worthwhile.

• Getting those initial few clients seems like the most difficult task, as if doing so will decide the fate of your company as a whole (it probably won't, and you shouldn't actually place that much emphasis on any one transaction).

Customers can smell fear, insecurity, and anxiety just like they can smell B.S. If you believe your product or service improves clients' lives, selling it should feel like a benevolent act of service, not a sleazy money-grab. If you're a sincere entrepreneur, prospects will believe your proposition; if you're apprehensive, they'll notice.

Approach every sale as if you're fine with or without it. This has improved my salesmanship, marketing skills, and mental health. When you put pressure on yourself to close a sale or convince a difficult prospect "or else" (your company will fail, your rent will be late, your electricity will be cut), you emit desperation and lower the quality of your pitch. There's no point.

5. The endless promises

We've all read a million times how to answer or disprove prospects' arguments and add extra incentives to speed or secure the close. Some objections shouldn't be refuted. What if I told you not to offer certain incentives, bonuses, and promises? What if I told you to walk away from some prospects, even if it means losing your sales goal?

If you market to enough people, make enough sales calls, or grow enough companies, you'll encounter prospects who can't be satisfied. These prospects have endless questions, concerns, and requests for more, more, more that you'll never satisfy. These people are a distraction, a resource drain, and a test of your ability to cut losses before they erode your sanity and profit margin.

To appease or convert these insatiably needy, greedy Nellies into customers, you may agree with or acquiesce to every request and demand — even if you can't follow through. Once you overpromise and answer every hole they poke, their trust in you may wane quickly.

Telling a prospect what you can't do takes courage and integrity. If you're honest, upfront, and willing to admit when a product or service isn't right for the customer, you'll gain respect and positive customer experiences. Sometimes honesty is the most refreshing pitch and the deal-closer.

6. No matter what

Have you ever said, "I'll do anything to close this sale"? If so, you've probably already been disqualified. If a prospective customer haggles over a price, requests a discount, or continues to wear you down after you've made three concessions too many, you have a metal hook in your mouth, not them, and it may not end well. Why?

If you're so willing to cut a deal that you cut prices, comp services, extend payment plans, waive fees, etc., you betray your own confidence that your product or service was worth the stated price. They wonder if anyone is paying those prices, if you've ever had a customer (who wasn't a blood relative), and if you're legitimate or worth your rates.

Once a prospect senses that you'll do whatever it takes to get them to buy, their suspicions rise and they wonder why.

• Why are you cutting pricing if something is wrong with you or your service?

• Why are you so desperate for their sale?

• Why aren't more customers waiting in line to pay your pricing, and if they aren't, what on earth are they doing there?

That's what a prospect thinks when you reveal your lack of conviction, desperation, and willingness to give up control. Some prospects will exploit it to drain you dry, while others will be too frightened to buy from you even if you paid them.

Walking down a two-way street. Be casual.

If we track each act of repulsion to an uneasiness, fear, misperception, or impulse, it's evident that these sales and marketing disasters were forced communications. Stiff, imbalanced, divisive, combative, bravado-filled, and desperate. They were unnatural and accepted a power struggle between two sparring, suspicious, unequal warriors, rather than a harmonious oneness of two natural, but opposite parties shaking hands.

Sales should be natural, harmonious. Sales should feel good for both parties, not like one party is having their arm twisted.

You may be doing sales wrong if it feels repulsive, icky, or degrading. If you're thinking cringe-worthy thoughts about yourself, your product, service, or sales pitch, imagine what you're projecting to prospects. Don't make it unpleasant, repulsive, or cringeworthy.

Hiring is difficult, but you shouldn't compromise on team members. Or it may suggest you need to look beyond years in a similar role/function.

Every hire should be someone we'd want as one of our first ten employees.

If you hire such people, your team will adapt, initiate, and problem-solve, and your company will grow. You'll stay nimble even as you scale, and you'll learn from your colleagues.

If you only hire for a specific role or someone who can execute the job, you'll become a cluster of optimizers, and talent will depart for a more fascinating company. A startup is continually changing, therefore you want individuals that embrace it.

As a leader, establishing ideal conditions for talent and having a real ideology should be high on your agenda. You can't eliminate attrition, nor would you want to, but you can hire people who will become your company's leaders.

In my last four jobs I was employee 2, 5, 3, and 5. So while this is all a bit self serving, you’re the one reading my writing — and I have some experience with who works out in the first ten!

First, we'll examine what they do well (and why they're beneficial for startups), then what they don't, and how to hire them.

First 10 are:

• Business partners: Because it's their company, they take care of whatever has to be done and have ideas about how to do it. You can rely on them to always put the success of the firm first because it is their top priority (company success is strongly connected with success for early workers). This approach will eventually take someone to leadership positions.
  

• High Speed Learners: They process knowledge quickly and can reach 80%+ competency in a new subject matter rather quickly. A growing business that is successful tries new things frequently. We have all lost a lot of money and time on employees who follow the wrong playbook or who wait for someone else within the company to take care of them.
  

• Autodidacts learn by trial and error, osmosis, networking with others, applying first principles, and reading voraciously (articles, newsletters, books, and even social media). Although teaching is wonderful, you won't have time.
  

• Self-scaling: They figure out a means to deal with issues and avoid doing the grunt labor over the long haul, increasing their leverage. Great people don't keep doing the same thing forever; as they expand, they use automation and delegation to fill in their lower branches. This is a crucial one; even though you'll still adore them, you'll have to manage their scope or help them learn how to scale on their own.
  

• Free Range: You can direct them toward objectives rather than specific chores. Check-ins can be used to keep them generally on course without stifling invention instead of giving them precise instructions because doing so will obscure their light.
  

• When people are inspired, they bring their own ideas about what a firm can be and become animated during discussions about how to get there.
  

• Novelty Seeking: They look for business and personal growth chances. Give them fresh assignments and new directions to follow around once every three months.

Here’s what the First Ten types may not be:

• Domain specialists. When you look at their resumes, you'll almost certainly think they're unqualified. Fortunately, a few strategically positioned experts may empower a number of First Ten types by serving on a leadership team or in advising capacities.
  

• Balanced. These people become very invested, and they may be vulnerable to many types of stress. You may need to assist them in managing their own stress and coaching them through obstacles. If you are reading this and work at Banza, I apologize for not doing a better job of supporting this. I need to be better at it.
  

• Able to handle micromanagement with ease. People who like to be in charge will suppress these people. Good decision-making should be delegated to competent individuals. Generally speaking, if you wish to scale.

Great startup team members have versatility, learning, innovation, and energy. When we hire for the function, not the person, we become dull and staid. Could this person go to another department if needed? Could they expand two levels in a few years?

First Ten qualities and experience level may have a weak inverse association. People with 20+ years of experience who had worked at larger organizations wanted to try something new and had a growth mentality. College graduates may want to be told what to do and how to accomplish it so they can stay in their lane and do what their management asks.

Does the First Ten archetype sound right for your org? Cool, let’s go hiring. How will you know when you’ve found one?

• They exhibit adaptive excellence, excelling at a variety of unrelated tasks. It could be hobbies or professional talents. This suggests that they will succeed in the next several endeavors they pursue.
  

• Successful risk-taking is doing something that wasn't certain to succeed, sometimes more than once, and making it do so. It's an attitude.
  

• Rapid Rise: They regularly change roles and get promoted. However, they don't leave companies when the going gets tough. Look for promotions at every stop and at least one position with three or more years of experience.

You can ask them:

• Tell me about a time when you started from scratch or achieved success. What occurred en route? You might request a variety of tales from various occupations or even aspects of life. They ought to be energized by this.
  

• What new skills have you just acquired? It is not required to be work-related. They must be able to describe it and unintentionally become enthusiastic about it.
  

• Tell me about a moment when you encountered a challenge and had to alter your strategy. The core of a startup is reinventing itself when faced with obstacles.
  

• Tell me about a moment when you eliminated yourself from a position at work. They've demonstrated they can permanently solve one issue and develop into a new one, as stated above.
  

• Why do you want to leave X position or Y duty? These people ought to be moving forward, not backward, all the time. Instead, they will discuss what they are looking forward to visiting your location.
  

• Any questions? Due to their inherent curiosity and desire to learn new things, they should practically never run out of questions. You can really tell if they are sufficiently curious at this point.

People who see their success as being the same as the success of the organization are the best-case team members, in any market. They’ll grow and change with the company, and always try to prioritize what matters. You’ll find yourself more energized by your work because you’re surrounded by others who are as well. Happy teambuilding!