Core Insights - The report indicates that large models are transitioning from experimental phases to practical applications, with 45% of surveyed companies deploying them in production environments [1][35][37] - Engineering R&D, customer support, and marketing are identified as the most active areas for AI deployment [35][37] Usage of Large Models - Only 45% of respondents use large models in production, while 23% use them for prototyping and 27% for information retrieval [4] - The majority of respondents (66%) expect AI to be utilized in engineering and R&D over the next 12 months, followed by customer support (37%) and sales (33%) [10] Payment Models for AI - 32% of respondents build customized large models, 27% purchase standard API services, and 25% utilize both options, while 16% do not pay for services [7] Challenges in Using Large Models - The most cited challenge (55%) is the insufficient knowledge level of large models [13] - Concerns about models becoming ineffective and high costs are also significant challenges, with half of the respondents highlighting these issues [14][15] Competitive Landscape - ChatGPT maintains a leading position in the large model market, followed by Gemini and Claude, while users typically engage with an average of 4.7 different models, indicating a highly competitive environment [18][37] - OpenAI remains dominant, but Google’s Gemini and Deepseek show the fastest progress, while Claude and Llama are perceived to be lagging [22] Acceptance of Chinese Models - 55% of respondents are open to using Chinese large models, but prefer them to be deployed outside of China, particularly in Europe and the US [27] Hardware for Training Large Models - NVIDIA holds a significant market share (78%) in training hardware, followed by Google’s TPU and AMD [29] Multi-modal Applications - OpenAI's models are frequently used for language generation, but users emphasize the importance of voice stability and quality [31] - In video generation tasks, adherence to prompts and cost are critical factors for users [33]

Overnight Microsoft (NASDAQ: MSFT) received a rather uncommon price target: not applicable. Specifically, KeyBanc’s Jackson Ader removed the technology giant’s previous target of $575 due to heightened sector and overall uncertainty.Furthermore, Ader downgraded MSFT stock’s rating from ‘overweight’ – ‘buy’ – to ‘sector weight’ – ‘neutral’ – explaining that the ongoing economic situation is reducing flexibility while increasing pressures on the technology giant’s margins.Microsoft has been generously spendin ...