quiz bu lëkkale ak tegtal · Diggante Niveau

Quiz ci modelu kodu kontekst bu guddu IA luxus

Saytu xeetu LTM yu Magic, seet ci muy lu yàgg, jàngat HashHop, xalaat ci codebase, ak jafe-jafe njëg yi seen algorithm toppalante di wut.

Yooni njiit yu jëm ciModèlu kodu kontekst bu gudd IA luxus
Laaj 1 de 8

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

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  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
    • Lu ëpp 100 milioŋ ciy jeton
    • 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. Lan moo waral bàyyi xel ci transformatër bu xamadi nekk jafe-jafe ci 100 milioŋ ciy token?
    • Du fay dara
    • Du dox ludul ci net bi
    • Dafay efaase dugal bi
    • Dafay eskale quadratically ak guddaayi sequence, mu nekk lu seer lool
  5. Ban liggéeyukaay la Magic jëflante ak moom ci 2024 ngir defar ay super ordinatër?
    • Google Cloud
    • Apple
    • Spotify
    • Adobe
  6. What does a larger context window make possible for a coding task?
    • Bind bu gëna gaaw ci klaweer
    • Include more cross-file code and documentation in one context, without guaranteeing project-wide correctness
    • Dayo ekraŋ bu gëna baax
    • Factures kuuraŋ yu yomb
  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