Jundo
57.4K posts

Jundo
@JundoYaps
Tìm kiếm bình yên giữa chốn đông người. 🍃1% năng lượng tích cực mỗi ngày. ☀️Sống cho hiện tại, không nghĩ về tương lai











Chào buổi sáng cùng crypto🌞 🕔Báo thức uy tín nhất sáng nay gọi tên ethereum:0xde4ee8057785a7e8e800db58f9784845a5c2cbd6 Nhìn cây nến khung tháng mà muốn tắt app đi ngủ tiếp. Đỉnh này thì anh em dám cản tàu không hay né gấp?

Any company can take on an effort to replace software. I am more inclined to be supportive if it's custom software. If so, one will need to rethink the workflow, train the model for user and enterprise context, agentify it. If done right it will have the property of increasing data integrity and also providing an ability to create enterprise context and intelligence over time which can significantly improve outcomes. The tools to do so are still nascent and evolving, mostly because models are expanding their capabilities and remit across memory, eval et al. Also, there is no backward compatibility on model embedding, a new model appears and the entire exercise on eval etc needs to be repeated. If enterprises are attempting to replace packaged software, I would caution against that, packaged software will get reimagined as an AI application by new startups as technology stabilizes. The challenge is as always the availability of competent resources who can architect an agile, AI first backend infrastructure. If you don't try though, you won't learn and be ready.


























