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There are a number of sizes listed below that appear to be quite similar, and while the tolerances of these connectors are typically indicated as ±0.05 or ±0.03 mm by the manufacturers, there is still ambiguity as to whether two sizes differing by only 0.05 mm (or where the specification is only given to the nearest 0.10 mm) warrants listing ...
ChatGPT is a generative artificial intelligence chatbot developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [2]
The interface dimensions for SMA connectors are listed in MIL-STD-348. [5] The SMA connector employs a 1 ⁄ 4 inch diameter, 36-thread-per-inch threaded barrel. The male is equipped with a hex nut measuring 5 ⁄ 16 inch (0.3125 inch / 7.9 mm) across opposite flats, thus taking the same wrench as a #6 SAE hex nut.
On 4 January 2012, Samsung announced in Singapore the launch for February 2012 at a price of S$898 (US$695). [ 4 ] The Galaxy Tab 7.7 Wi-Fi was on sale in Australia on 13 January 2012, with prices approximately A$550.
A 3.5 mm phone connector A 3.5 mm 4-conductor TRRS phone connector A 3.5 mm 5-conductor TRRRS phone connector. In the most common arrangement, consistent with the original intention of the design, the male plug is connected to a cable, and the female socket is mounted in a piece of equipment.
Its API costs $0.15 per million input tokens and $0.6 per million output tokens, compared to $2.50 and $10, [19] respectively, for GPT-4o. It is also significantly more capable and 60% cheaper than GPT-3.5 Turbo, which it replaced on the ChatGPT interface. [ 18 ]
The Note 10 and Note 10+ are the first mainstream Samsung smartphones to omit the 3.5 mm headphone jack, which earned Samsung criticism for mocking the iPhone 7's lack of the headphone jack on the Galaxy Note 7 UNPACKED keynote in August 2016 [7] [11] – Samsung said it used the extra space for more battery. [12]
Lambdalabs estimated a hypothetical cost of around $4.6 million US dollars and 355 years to train GPT-3 on a single GPU in 2020, [16] with lower actual training time by using more GPUs in parallel. Sixty percent of the weighted pre-training dataset for GPT-3 comes from a filtered version of Common Crawl consisting of 410 billion byte-pair ...