PLOT_STEPS = 55 x_ = np.linspace(-5, 5, 500) y_ = np.linspace(-2.2, 2.2, 500) X, Y = np.meshgrid(x_, y_) Z = loss(X, Y) fig = plt.figure(figsize=(16, 10), facecolor=”#FAFAF8″) gs = GridSpec(2, 3, figure=fig, hspace=0.45, wspace=0.38, left=0.07, right=0.97, top=0.88, bottom=0.08) COLORS = { “gd”: “#E05C4B”, “mom_good”: “#3A7CA5”, “mom_large”: “#F4A536”, “contour”: “#D4C9B8”, “minima”: “#2A9D5C”, “start”: “#444444”, } PANEL_TITLES…
If you’ve ever built a production AI pipeline that runs long jobs — processing thousands of prompts overnight, kicking off a Deep Research agent, or generating a long video — you’ve almost certainly dealt with the polling problem. Your code sits in a loop, firing GET requests every few seconds asking, “Is the job done…
Former Andreessen Horowitz investor Katie Haun announced on Monday in a press release that her firm has raised $1 billion across new funds to continue its thesis of backing crypto and blockchain. The capital will be spread across startups at early and later stages, Bloomberg reported, and, within the crypto and blockchain space, it will be…
fig, axes = plt.subplots(2, 2, figsize=(14, 10)) colors_a = [“gray”, “#1f77b4”, “#ff7f0e”, “#2ca02c”, “#d62728″][: len(asmd_means)] axes[0, 0].bar(list(asmd_means.keys()), list(asmd_means.values()), color=colors_a) axes[0, 0].axhline(0.1, ls=”–“, color=”red”, label=”0.10 imbalance threshold”) axes[0, 0].set_title(“Mean ASMD across covariates”) axes[0, 0].set_ylabel(“Mean ASMD”); axes[0, 0].legend() axes[0, 0].tick_params(axis=”x”, rotation=20) truth = target_df[“happiness”].mean() colors_b = [“#888”] + [“#1f77b4”, “#ff7f0e”, “#2ca02c”, “#d62728”][: len(methods)] + [“black”] axes[0, 1].bar(list(outcome_means.keys()),…
When it comes to the specter of AI’s labor-displacing potential, Jensen Huang thinks that the American worker has nothing to fear. During a conversation Monday night with MSNBC’s Becky Quick hosted by the Milken Institute — an economic policy think tank, the jovial Nvidia CEO said that AI was an industrial-scale generator of jobs, not…
A extreme safety vulnerability affecting virtually each model of the Linux working system has caught defenders off-guard and scrambling to patch after safety researchers publicly launched exploit code that permits attackers to take full management of weak techniques. The U.S. authorities says the bug, dubbed “CopyFail,” is now being exploited in the wild, which means it’s…
Training and serving large transformer models at scale is fundamentally a memory management problem. Every GPU in a cluster has a fixed amount of VRAM, and as model sizes and context lengths grow, engineers constantly have to make trade-offs about how to distribute work across hardware. A new technique from Zyphra, called Tensor and Sequence…
Geothermal startup Fervo Energy said Monday it hopes to raise up to $1.3 billion in its initial public offering. The company would be valued at up to $6.5 billion if shares sell at the top of its $21 to $24 price target. That’s more than twice what Fervo had reportedly been seeking earlier this year…
Two days earlier than the Musk v. Altman trial started, Elon Musk requested OpenAI cofounder and president Greg Brockman about reaching a settlement. When Brockman instructed each side drop their claims, Musk responded, “By the tip of this week, you and Sam [Altman] would be the most hated males in America. When you insist, so…
@step(enable_cache=True) def load_data() -> Annotated[DatasetBundle, “raw_dataset”]: data = load_breast_cancer() return DatasetBundle( data.data, data.target, data.feature_names, stats={“source”: “sklearn.datasets.load_breast_cancer”}, ) @step def split_and_scale( bundle: DatasetBundle, test_size: float = 0.2, random_state: int = 42, ) -> Tuple[ Annotated[np.ndarray, “X_train”], Annotated[np.ndarray, “X_test”], Annotated[np.ndarray, “y_train”], Annotated[np.ndarray, “y_test”], ]: X_tr, X_te, y_tr, y_te = train_test_split( bundle.X, bundle.y, test_size=test_size, random_state=random_state, stratify=bundle.y, ) scaler…
