
Advancing AI with Multimodal LLMs: Insights from MM1
Bayyanar Makomar AI: Yadda Binciken Juyin Juya Halin MM1 na Apple ke Canza Multimodal Learning
Articles on AI, post-quantum cryptography, ISO 20022 and the future of payments.
TOPIC
Foundation models, multimodal LLMs (Gemini, Gemma, Mistral, MM1), prompt engineering, and the open-source releases that shape what banks can build inside their own data perimeter.

Bayyanar Makomar AI: Yadda Binciken Juyin Juya Halin MM1 na Apple ke Canza Multimodal Learning

Sake Fasalin Hulɗar Masu Amfani a Duk Harsunan

Duba Ciki kan Iyawa, Gudummawar Buɗaɗɗen Tushe, da Abin da ke Zuwa

Nazari Mai Zurfi na Babban Nasarar AI ta Google

Injiniyan prompt yana tsara shigar LLM a lokacin inference — ba tare da sabunta nauyi ba. Labarin yana rufe dabarun da aka tabbatar suna da inganci a 2024: zero-shot task framing (Brown et al., 2020), chain-of-thought reasoning (Wei et al., 2022), self-consistency sampling (Wang et al., 2022), ReAct agent loops (Yao et al., 2022), haɗarin indirect prompt injection (Greshake et al., 2023), da ƙirar RAG daga ayyukan kuɗi.

Shekara Mai Muhimmanci ga Fasaha, Al'umma, da Juyin ɗabi'a

Generative AI ya wuce daga bincike zuwa aiwatarwa a 2023. GPT-4, Claude 2, Llama 2, da Mistral sun nuna cewa large language models na iya sarrafa duba takardun shari'a, samar da code, da tattaunawar abokan ciniki a ingancin da ya dace da ɗan adam — wanda ya haifar da tambayoyin gaggawa na gudanarwa game da hallucination, zubewar bayanai, da bin ƙa'idoji a ayyukan kudi.