Browsing: Optimization

Liquid AI has released Antidoom, an open-source method that targets a common failure mode in reasoning models. That failure mode is the doom loop. In a…

One of the most useful things to understand about AI is that most of its use cases are an “optimization equation.” In other words, you’re always…

Getting prompts right is still the hardest part of shipping reliable LLM applications. Small wording changes can swing accuracy by 20 percent. What works on a…

In my previous post, I four core innovations that makes ORPilot a production-oriented open-source LLM-for-OR tool, namely interview agent, data collection agent, parameter computation agent and…

k = RUN_KNOBS train_out = run_cli([“python”,”scripts/train.py”,”–config”,CFG,”–split_dir”,SPLIT, “–optimizer_model”,OPTIMIZER_MODEL,”–target_model”,TARGET_MODEL,”–out_root”,RUN, *COMMON, “train.train_size=0″, f”train.num_epochs={k[‘num_epochs’]}”, f”train.batch_size={k[‘batch_size’]}”, f”gradient.minibatch_size={k[‘minibatch’]}”, f”gradient.merge_batch_size={k[‘merge_batch’]}”, f”gradient.analyst_workers={k[‘workers’]}”, f”optimizer.learning_rate={k[‘lr’]}”, f”optimizer.lr_scheduler={k[‘lr_sched’]}”, “optimizer.use_slow_update=true”, “optimizer.use_meta_skill=true”, f”env.workers={k[‘workers’]}”, f”env.limit={k[‘limit’]}”], “TRAIN (rollout->reflect->aggregate->select->update->gate; slow-update + meta-skill)”) import…

def make_problems(n, seed=0): rng = random.Random(seed) out = [] for _ in range(n): t = rng.choice([“discount”, “travel”, “wallet”, “chain”]) if t == “discount”: unit = rng.choice([40,…

to use AI to build a mathematical optimization model for a real business problem, you’ve probably run into the same wall: the AI works beautifully on…

factor_prices = load_factors_dataset() X_full, F_full = prices_to_returns(prices, factor_prices) X_tr, X_te, F_tr, F_te = train_test_split( X_full, F_full, test_size=0.33, shuffle=False ) fm = MeanRisk( objective_function=ObjectiveFunction.MAXIMIZE_RATIO, risk_measure=RiskMeasure.VARIANCE, prior_estimator=FactorModel(), )…

In this tutorial, we implement an advanced Bayesian hyperparameter optimization workflow using Hyperopt and the Tree-structured Parzen Estimator (TPE) algorithm. We construct a conditional search space…

past couple of years have seen a surge of investment in open‑source and commercial tabular foundation models built around in‑context learning (ICL). In 2025, for example,…