[1] https://www.marketwatch.com/story/how-profitable-is-apples-a...
1,298 karma · joined February 4, 2023
[1] https://www.marketwatch.com/story/how-profitable-is-apples-a...
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELE...
"Article 13: Anti-circumvention
4. The gatekeeper shall not engage in any behaviour that undermines effective compliance with the obligations of Articles 5, 6 and 7 regardless of whether that behaviour is of a contractual, commercial or technical nature, or of any other nature, or consists in the use of behavioural techniques or interface design.
7. Where the gatekeeper circumvents or attempts to circumvent any of the obligations in Article 5, 6, or 7 in a manner described in paragraphs 4, 5 and 6 of this Article, the Commission may open proceedings pursuant to Article 20 and adopt an implementing act referred to in Article 8(2) in order to specify the measures that the gatekeeper is to implement."
The DMA is 66 pages of legalese, otherwise I would have read it to find out:
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELE...
from https://developer.apple.com/support/dma-and-apps-in-the-eu/#...
I have not seen this important aspect mentioned yet. Once you have opted in to Apple's new business terms, you will be locked in to those terms forever.
Because of this restriction, given the ridiculous €0.50 per year per install fees, no developer who hopes their new app will one day have more than 1M installs will choose these new terms, and I have no doubt that is exactly Apple's intention here.
https://www.theverge.com/2023/11/6/23948990/and-were-on-to-s...
Courtesy of GPT4:
"To determine which option is cheaper, Gemini Pro or GPT-3.5 Turbo, we need to consider the average length difference between tokens and characters and the pricing structure for each.
Gemini Pro Pricing: Input: $0.00025 per 1,000 characters Output: $0.0005 per 1,000 characters
GPT-3.5 Turbo Pricing: Input: $0.0010 per 1,000 tokens Output: $0.0020 per 1,000 tokens
Average Length Difference Between Tokens and Characters: A token in GPT-3.5 can be a single word, part of a word, or a special character. On average, a token in GPT-3 models is roughly equivalent to 4 characters (this is a rough estimate as the length of tokens can vary significantly).
Given this information, let's calculate the effective cost per 1,000 characters for both Gemini Pro and GPT-3.5 Turbo. For GPT-3.5 Turbo, since 1 token ≈ 4 characters, the cost per 1,000 characters would be a quarter of the cost per 1,000 tokens. We'll calculate the cost for both input and output for each and compare.
The total cost per 1,000 characters for both Gemini Pro and GPT-3.5 Turbo, considering both input and output, is the same at $0.00075. Therefore, based on the provided pricing and the average token-to-character ratio, they are equally cost-effective."
Flutter: 46% React Native: 35% Unity: 10% Cordova: 10% Ionic: 9% Xamarin: 8%
Just one datapoint, of course - a survey of 26,384 developers.
They ran a battery of 12 tests and looked for one with a statistically significant difference at the 5% level.
If there were no actual differences, how many tests would you need to run to find at least one that by chance shows significance? If you run 20, you’d expect 5% to do so, on average, which is 1. Running 12 and finding 1 is not a significant finding.
Then, suspiciously, the only statistically significant cognitive test improvement they found was on trial 5 of a verbal learning test, which showed little to no improvement on any of the other trials. That makes no sense.
Finally the brain changes had a p-value of 0.046, which is barely significant by even the weak 5% threshold, and the brain changes weren’t correlated with the test result improvements.
Perhaps interesting, but only if replicated.
Then suspiciously, they found one significant result on trial 5 of the verbal learning test but little to no improvement on the other trials. That makes no sense.
Finally the brain changes had a p-value of 0.046, which is barely significant by even the weak 5% threshold, and the changes weren’t correlated with the test result improvements.
Perhaps interesting but only if replicated.
Unrelatedly, I would not have believed you at the time if you told me that the then CEO had entered into an illegal mutual non-solicit agreement with Apple (and Intel, Adobe, and others), suppressing employee pay by agreeing not to recruit or hire each other's workers. History and a successful class action lawsuit revealed a different story.
"Do NOT delete any emails. <chuckles>. Let me say that again to make sure everyone has understood me correctly: do NOT delete any emails!"
The way it was said, the chuckle, and the way it was repeated with the extra emphasis on NOT, sent a clear message: delete all such emails.
As it turns out, I do have one T, so I have another really good reason to avoid alcohol entirely - and also to take krill oil, quercetin, resveratrol/pterostilbene, D3, K2, the Bs, and lithium (the recommendations from the study you linked).
"In this updated systematic review and meta-analysis, daily low or moderate alcohol intake was not significantly associated with all-cause mortality risk, while increased risk was evident at higher consumption levels, starting at lower levels for women than men."
Cognitive decline and dementia are multifactorial, and with alcohol consumption there are trade-offs between neuronal death, potential improvements in vascular function, and other things known and as yet unknown.
Here's an interesting recent finding from a study of 20K BioBank participants: "Alcohol consumption above 7 units weekly associated with higher brain iron. Iron accumulation represents a potential mechanism for alcohol-related cognitive decline."
https://journals.plos.org/plosmedicine/article?id=10.1371/jo...
There is some functional recovery after abstention from alcohol consumption due to regrowth of synapses and neuroplasticity, much in the same way our brains can partially recover from a stroke even though the neurons in the part of the brain that was deprived of oxygen are permanently lost. However the recovery is not complete and some of the loss of brain volume is in fact permanent.
Firstly, it's important to consider neuroplasticity, which is the brain's ability to reorganize itself by forming new connections between neurons. Even though the number of neurons may not increase, the brain can adapt and compensate for the loss by strengthening existing connections or forming new ones, leading to an overall improvement in cognitive function.
Secondly, alcohol impairs cognitive function through various mechanisms other than neuronal death. For instance, alcohol disrupts sleep quality, which in turn impairs cognitive function. When someone stops consuming alcohol, their sleep quality is likely to improve, leading to better cognitive performance.
Lastly, regular repeated brain insult from alcohol consumption leads to chronic cognitive deficits, as the brain is consistently affected by alcohol's neurotoxic effects. When alcohol consumption ceases, the continuous damage stops, allowing the brain to recover to a certain extent, even without replacing the lost neurons.
In conclusion, the statements in my original comment are not conflicting. Improved cognitive abilities after quitting alcohol can be attributed to factors such as neuroplasticity, improved sleep quality, and the cessation of ongoing damage to the brain.
For me the primary reason to stop drinking was preservation of brain cells. Recent studies have shown a simple dose response relationship between neuronal death and alcohol consumption, with no minimum threshold. Even one drink will kill a few. They don’t grow back.
Since quitting in 2021, I have become noticeably sharper, my code quality has improved, and I feel better. I do not miss it at all.
main: seed = 1678990693 llama_model_load: loading model from 'ggml-alpaca-7b-q4.bin' - please wait ... llama_model_load: ggml ctx size = 4529.34 MB llama_model_load: memory_size = 512.00 MB, n_mem = 16384 llama_model_load: loading model part 1/1 from 'ggml-alpaca-7b-q4.bin' llama_model_load: .................................... done llama_model_load: model size = 4017.27 MB / num tensors = 291
system_info: n_threads = 4 / 32 | AVX = 1 | AVX2 = 1 | AVX512 = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | VSX = 0 | main: interactive mode on. sampling parameters: temp = 0.100000, top_k = 40, top_p = 0.950000, repeat_last_n = 64, repeat_penalty = 1.300000
== Running in chat mode. == - Press Ctrl+C to interject at any time. - Press Return to return control to LLaMa. - If you want to submit another line, end your input in '\'.
> What is an alpaca? An Alpaca (Vicugna pacos) is one of two species in the genus Vicuña, which are both domesticated animals from South America and Central Asia that have been bred for their fine wool. >