Skybox AI is a free 360° image generator. Use the power of AI to imagine stunning worlds in seconds and fine tune them for use in immersive VR, XR, or games.
“Memory colors are colors that are universally associated with specific objects, elements or scenes in our environment. They are the colors that we expect to see in specific situations: these colors are based on our expectation of how certain objects should look based on our past experiences and memories.
For instance, we associate specific hues, saturation and brightness values with human skintones and a slight variation can significantly affect the way we perceive a scene.
Similarly, we expect blue skies to have a particular hue, green trees to be a specific shade and so on.
Memory colors live inside of our brains and we often impose them onto what we see. By considering them during the grading process, the resulting image will be more visually appealing and won’t distract the viewer from the intended message of the story. Even a slight deviation from memory colors in a movie can create a sense of discordance, ultimately detracting from the viewer’s experience.”
Sam Altman, CEO of OpenAI, dropped a 💣 at a recent MIT event, declaring that the era of gigantic AI models like GPT-4 is coming to an end. He believes that future progress in AI needs new ideas, not just bigger models.
So why is that revolutionary? Well, this is how OpenAI’s LLMs (the models that ‘feed’ chatbots like ChatGPT & Google Bard) grew exponentially over the years: ➡️GPT-2 (2019): 1.5 billion parameters ➡️GPT-3 (2020): 175 billion parameters ➡️GPT-4: (2023): amount undisclosed – but likely trillions of parameters
That kind of parameter growth is no longer tenable, feels Altman.
Why?: ➡️RETURNS: scaling up model size comes with diminishing returns. ➡️PHYSICAL LIMITS: there’s a limit to how many & how quickly data centers can be built. ➡️COST: ChatGPT cost over over 100 million dollars to develop.
What is he NOT saying? That access to data is becoming damned hard & expensive. So if you have a model that keeps needing more data to become better, that’s a problem.
Why is it becoming harder and more expensive to access data?
🎨Copyright conundrums: Getty Images, individual artists like Sarah Andersen, Kelly McKernan & Karloa Otiz are suing AI companies over unauthorized use of their content. Universal Music asked Spotify & Apple Music to stop AI companies from accessing their songs for training.
🔐Privacy matters & regulation: Italy banned ChatGPT over privacy concerns (now back after changes). Germany, France, Ireland, Canada, and Spain remain suspicious. Samsung even warned employees not to use AI tools like ChatGPT for security reasons.
💸Data monetization: Twitter, Reddit, Stack Overflow & others want AI companies to pay up for training on their data. Contrary to most artists, Grimes is allowing anyone to use her voice for AI-generated songs … for a 50% profit share.
🕸️Web3’s impact: If Web3 fulfills its promise, users could store data in personal vaults or cryptocurrency wallets, making it harder for LLMs to access the data they crave.
🌎Geopolitics: it’s increasingly difficult for data to cross country borders. Just think about China and TikTok.
😷Data contamination: We have this huge amount of ‘new’ – and sometimes hallucinated – data that is being generated by generative AI chatbots. What will happen if we feed that data back into their LLMs?
No wonder that people like Sam Altman are looking for ways to make the models better without having to use more data. If you want to know more, check our brand new Radar podcast episode (link in the comments), where I talked about this & more with Steven Van Belleghem, Peter Hinssen, Pascal Coppens & Julie Vens – De Vos. We also discussed Twitter, TikTok, Walmart, Amazon, Schmidt Futures, our Never Normal Tour with Mediafin in New York (link in the comments), the human energy crisis, Apple’s new high-yield savings account, the return of China, BYD, AI investment strategies, the power of proximity, the end of Buzzfeed news & much more.
OpenAI, the corporation behind ChatGPT, has announced plans to introduce a new watermarking feature to help Google detect AI generated text. Watermarked text in ChatGPT will include cryptography in the form of embedding a word pattern, letters, and punctuation in the form of a secret code.
“Disney+ and its other two services, ESPN+ and Hulu, together trimmed losses by $228 million, or 13%, from a year earlier to $659 million. The improvement from the previous quarter was even greater, as it trimmed losses by nearly $400 million from $1.1 billion.
Disney did it with a 2% drop in subscribers for Disney+ to 157.8 million, and a 1% drop in subscribers overall, when including ESPN+ and Hulu in subscription totals. It was able to trim losses with fewer subscribers through higher subscription revenue and a decrease in marketing costs, partially offset by higher programming and production costs. “
“Disney has announced plans to combine content from its Disney+ and Hulu streaming services in the US.
The move comes after Disney+ lost four million subscribers in the first three months of the year, and the firm is under pressure to make its streaming business profitable
It now has a total of more than 231 million subscriptions across its three streaming platforms, which also include the sports-focused ESPN+ and wider entertainment site Hulu. Disney+ has close to 158m subscribers around the world, although that is still behind rival Netflix’s 232.5m subscribers.
The latest announcement comes after thousands of Hollywood TV and movie screenwriters held their first strike in 15 years last week. They are calling for better pay and working conditions as the transition to streaming has upended the traditional television and film industry. The last writers’ strike was in 2007. It lasted 100 days and cost the industry an estimated $2bn.”
To measure the contrast ratio you will need a light meter. The process starts with you measuring the main source of light, or the key light.
Get a reading from the brightest area on the face of your subject. Then, measure the area lit by the secondary light, or fill light. To make sense of what you have just measured you have to understand that the information you have just gathered is in F-stops, a measure of light. With each additional F-stop, for example going one stop from f/1.4 to f/2.0, you create a doubling of light. The reverse is also true; moving one stop from f/8.0 to f/5.6 results in a halving of the light.
