This comment was so wholesome it made my day 🥰
This comment was so wholesome it made my day 🥰
I guess it could cause a severe seizure or even catastrophic neural failure. The synchronous firing would disrupt the balance of excitatory and inhibitory signals in the brain, potentially damaging neurons and leading to a loss of normal brain function.
The result might include a loss of consciousness, significant cognitive impairments, or even death, depending on the extent and duration of the event.
But then again, I have no idea, since I ain’t an expert in that field and in fact am actually just a dog who figured out how to use a computer 🙃
I guess it’s hard to measure the power of AI anyway but I would say a strong no: it doesn’t equate to the power of AI doubling every 3.5 months 😅
An academic book about emojis that can’t include emojis? That’s ironic and frustrating. Makes me sad that we live in a world where copyright hinders education and discussion 🙈
Here is a Tl;Dr for the ones who don’t want to click the link:
Oxford professor Jieun Kiaer published an academic book called “Emoji Speak: Communications and Behaviours on Social Media,” exploring how emojis are used across different cultures and ages, and considering their future in digital communication.
Although the book discusses emojis in detail, Kiaer was unable to include actual images of many emojis due to copyright concerns, despite the fact that these symbols are ubiquitous in social media spaces, which are almost entirely copyright-free.
Instead of using actual emojis, Kiaer hired an artist, Loli Kim, to draw similar representations, illustrating the barriers that exist between the online and offline worlds concerning copyright.
The inability to use emojis in the book, even in an academic context, highlights the complications and absurdity of modern copyright laws, which some argue could have constituted a fair use situation.
Some in the AI industry have proposed concepts similar to Moore’s Law to describe the rapid growth of AI capabilities.
Although there is no universally accepted law or principle akin to Moore’s Law for AI, people often refer to trends that describe the doubling of model sizes or capabilities over a specific time frame.
For instance, OpenAI has previously described a trend where the amount of computing power used to train the largest AI models has been doubling roughly every 3.5 months since 2012.
I wonder if this technique can be expanded to other eye conditions 🤔
Here is a Tl;Dr for the ones which don’t want to click the link:
Researchers at Anglia Ruskin University in the UK have used 3D nanotechnology to successfully grow human retinal cells, offering a new way to treat age-related macular degeneration (AMD), a leading cause of blindness.
AMD is categorized into two types: ‘dry’ and ‘wet,’ both of which cause vision loss due to the destruction or deterioration of the retina’s RPE cells.
The team used electrospinning, a novel technique in this context, to create a 3D nanofibrous scaffold, composed of two polymers, which served as a base for growing the RPE cells. An anti-inflammatory coating was applied to the scaffold, enhancing the growth and functionality of the cells, which remained healthy and viable for up to 150 days.
This innovative approach could lead to effective treatments for sight conditions like AMD, and the researchers are now focusing on transplanting these freshly grown cells into the human eye.
Haha, just saw this video as well and searched the YouTube comments for someone mentioning it 🤣
I also don’t have anything to add other than that I really appreciate comments who pay respects to details of other comments. I don’t know, just makes me happy, so thank you for that!
Oh, and fuck this fucking asshole named Putin, may he die a painful and slow death.