Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya Miundo ya Misimbo ya Muktadha Mrefu ya AI

Gundua miundo ya LTM ya Uchawi, urejeshaji wa muktadha mrefu, tathmini za HashHop, hoja za msingi wa kanuni, na tatizo la gharama malengo yao ya algorithm ya mfuatano.

Njia za mwongozo zinazohusianaMitindo mirefu ya Msimbo wa Muktadha wa AI
Swali 1 ya 8

What software-development direction has Magic said it is pursuing?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. What software-development direction has Magic said it is pursuing?
    • Developing AI models and agents for software-engineering tasks
    • Replacing all software repositories with image datasets
    • Building a spreadsheet-only OCR service
    • Generating code without considering project context
  2. What maximum context capacity did Magic announce for LTM-2-mini in August 2024?
    • Up to 100 thousand tokens
    • Hadi tokeni milioni 100
    • Up to 1 million tokens
    • Up to 10 billion tokens
  3. What does Magic use HashHop to evaluate?
    • How well a model predicts a familiar fact from pretraining
    • Whether generated source code passes every production test
    • Retrieval and chaining over random hash pairs placed in a supplied long context
    • How quickly a model compiles a new programming language
  4. Kwa nini umakini wa kibadilishaji cha ujinga ni shida kwa muktadha wa ishara ya milioni 100?
    • Haigharimu chochote
    • Inafanya kazi nje ya mtandao pekee
    • Inafuta ingizo
    • Inakua mara nne na urefu wa mfuatano, na kuwa ghali sana
  5. Ni kampuni gani ambayo Magic ilishirikiana nayo mnamo 2024 kuunda kompyuta kuu?
    • Google Wingu
    • Apple
    • Spotify
    • Adobe
  6. What does a larger context window make possible for a coding task?
    • Kuandika kwa haraka kwenye kibodi
    • Include more cross-file code and documentation in one context, without guaranteeing project-wide correctness
    • Azimio bora la skrini
    • Bili za bei nafuu za umeme
  7. What comparison did Magic report for LTM-2-mini’s sequence-dimension algorithm?
    • A 1,000-fold improvement in total cost for every deployed model
    • A 1,000-fold increase in the accuracy of all code edits
    • About 1,000 times lower per-token algorithmic cost than Llama 3.1 405B attention at 100M context in the reported configuration
    • A fixed 1,000-token limit for every LTM model
  8. In a simple illustrative lookup with A → B, B → C, and C → D, what chain follows from A?
    • A → C → B → D
    • A → B → D → C
    • A → D → C → B
    • A → B → C → D