• 38 Posts
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Joined 2 年前
Cake day: 2023年7月2日
  • foggytoNot The Onion•OpenAI just launched its new ChatGPT Agent that can make as many as 1 complicated cupcake order per hour, but even Sam Altman says you probably shouldn't trust it for 'high-stakes uses'English
    1·
    1 小时前

    Lots of questions. Any of which I could only provide a very opinionated answer on. But to answer the bulk of your response here, I think we look to sociologists to predict the future of AI integrating into the division of labor.

    Basically, the division of labor will become more organic and complex, less rigid and mechanical.

    (i.e. nobody was paying bills by walking the neighborhood dogs in 1920. As technology increases, the division of labor becomes more organic/less mechanical.)

    So with this Is say that “Software Developer” is not a job in the future, but that statement carries more weight than it should. The software developer of today will be invaluable as a technician working with AI. In this example “software developer” is a mechanical division of labor where something in the future might be like “Development Strategist” as a more organic division of labor. As to what that looks like, your guess is as good as mine.

  • foggytoNot The Onion•OpenAI just launched its new ChatGPT Agent that can make as many as 1 complicated cupcake order per hour, but even Sam Altman says you probably shouldn't trust it for 'high-stakes uses'English
    66·
    2 小时前

    Okay, down vote away. Lemmy has such an ignorant hate boner against AI.

    Computers were fucking trash in the 50s. Dumb tech enthusiasts all said the same shit people say about AI today: computers are unreliable, create more problems than they solve, are ham-fisted solutions to problems that require human interaction, etc. here are the HUGE problems computers had that we solved before the 70s.

    1. Signed Number Representation

    Problem: No standard way to represent negative numbers in binary.

    Solution: Two’s complement became the standard.

    1. Error Detection & Correction

    Problem: Bit errors from unreliable hardware.

    Solution: Hamming codes, CRC, and other ECC methods.

    1. Floating Point Arithmetic

    Problem: Inconsistent and error-prone real number math.

    Solution: IEEE 754 standardized floating-point formats and behavior.

    1. Instruction Set Standardization

    Problem: Each computer had its own incompatible instruction set.

    Solution: Standardized ISAs like x86 and ARM became dominant.

    1. Memory Access and Management

    Problem: Memory was slow, small, and expensive.

    Solution: Virtual memory, caching, and paging systems.

    1. Efficient Algorithms

    Problem: Basic operations like sorting were inefficient.

    Solution: Research produced efficient algorithms (e.g., Quicksort, Dijkstra’s).

    1. Circuit Logic Design

    Problem: No formal approach to designing logic circuits.

    Solution: Boolean algebra, Karnaugh maps, and FSMs standardized design.

    1. Program Control Flow

    Problem: Programs used unstructured jumps and were hard to follow.

    Solution: Structured programming and control constructs (if, while, etc.).

    1. Character Encoding

    Problem: No standard way to represent letters or symbols.

    Solution: ASCII and later Unicode standardized text encoding.

    1. Programming Languages and Compilation

    Problem: Code was written in raw machine or assembly code.

    Solution: High-level languages and compilers made programming more accessible.

    Its just ignorant to be acting like any of the problems we face with AI won’t be sorted just as they were with computers.