= output_tensor((ndim,), "int64") for i in const_range(ndim): if i != axis: out[i] = inputs[0][i] for j in const_range(1, len(inputs)): assert out[i] == inputs[j][i] in the inputs of concatenate." else: out[i] = int64(0) for j in const_range(len(inputs)): out[i] += inputs[j][i] return out Shape function example Use hybrid

Intelligence93 Artificial General Intelligence, or AGI, refers to systems capable of performing the full range of human intellectual tasks – reasoning, planning, learning from small data samples, and generalizing or application-specific integrated circuits. Unlike GPUs, which are designed to support a wide range of workloads, ASICs are purpose-built to handle specific computational tasks with maximum efficiency Investment Levels = Good News for Consumers…Others TBD…179 …Revenue-per-User Multiple – OpenAI = In-the-Range Note: OpenAI figures are estimates as of 4/25. All other public-company figures are as of 12/31/24

model with human preference and produce DeepSeek-V2 Chat (RL). We evaluate DeepSeek-V2 on a wide range of benchmarks in English and Chinese, and compare it with representative open-source models. Evaluation enable our model to support multiple modalities, enhancing its versatility and utility in a wider range of scenarios. References AI@Meta. Llama 3 model card, 2024. URL https://github.com/meta-llama/llama3/bl assert is_not_prime(35) == True [BEGIN] import math def is_not_prime(n): result = False for i in range(2,int(math.sqrt(n)) + 1): if n % i == 0: result = True return result [DONE] You are an expert Python

certainty. A higher Gemini temperature setting is like a high softmax temperature, making a wider range of temperatures around the selected setting more acceptable. This increased uncertainty accommodates selects the top tokens whose cumulative probability does not exceed a certain value (P). Values for P range from 0 (greedy decoding) to 1 (all tokens in the LLM’s vocabulary). The best way to choose between

= var(“n”) A = bind_buffer(shape=[n], a) B = bind_buffer(shape=[n], b) for i in iter_range(n, iter_type=”data_par”): A[i] = B[i] + 1
 
 mod = tvm.IRModule([te_add_one]) print(mod[”te_add_one”]

fill in forms, and gather data just like a human would. It can also run processes across a wide range of tools and systems—no need for custom integrations or APIs. Enterprises use it to automate workflows