Tumor tissue engineering has opened new avenues for cancer research. With an emphasis on gastrointestinal malignancies, we summarize capabilities and limitations of patient-derived and engineered organoid models. We then discuss how innovations in biomaterial design, biofabrication, microfluidics, benchmarking, and AI converge to better emulate tumor tissues and advance translational modeling.
Timestamps:
00:00 — New Way Of Computing
06:46 — How It Works
09:39 — Outlook.
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Luke Dicken, who previously spent a decade with Zynga, says his time with the company “has come to an end”
Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a study published in Physical Review Letters, a team led by Prof. Peng Xinhua and Assoc. Prof. Li Zhaokai from the University of Science and Technology of China of the Chinese Academy of Sciences demonstrated that a quantum processor comprising just nine interacting spins outperforms classical networks with thousands of nodes in realistic weather forecasting tasks.
By exploiting unique quantum features such as superposition and entanglement, quantum devices offer new ways to represent and process information.
Recent experiments have shown their advantages in specialized benchmark tasks, but extending these gains to real-world applications remains a challenge. In particular, many quantum approaches rely on complex circuits that are difficult to implement accurately on today’s noisy hardware.
In a recent study published in Nature Communications, researchers created a memristor that uses a built-in oxygen gradient to produce slow, stable conductance changes, enabling a reinforcement learning (RL) algorithm to learn faster and more stably than conventional approaches.
Reinforcement learning stands as one of the most promising ways to achieve continual learning in AI. The idea is to replicate how biological systems acquire and adapt knowledge slowly over time. The brain achieves this via ion gradients that regulate slow, directional signaling across cell membranes. Replicating this in hardware is a key goal of neuromorphic computing.
With their ability to mimic synaptic behavior, memristors have long been considered strong candidates for this. However, most existing devices suffer from unpredictable, abrupt conductance changes, making sustained and stable learning difficult.
Threat actors are exploiting the recent Claude Code source code leak by using fake GitHub repositories to deliver Vidar information-stealing malware.
Claude Code is a terminal-based AI agent from Anthropic, designed to execute coding tasks directly in the terminal and act as an autonomous agent, capable of direct system interaction, LLM API call handling, MCP integration, and persistent memory.
On March 31, Anthropic accidentally exposed the full client-side source code of the new tool via a 59.8 MB JavaScript source map included by accident in the published npm package.
Jack Dorsey (Block CEO) and Roelof Botha (Sequoia partner and Block board member) on Rewriting the CEO playbook for the AI era.
• Manager mode = Pyramid (command & control)
• Founder mode = Flat (founders decide fast)
• Dorsey mode = Circle w/ AI at the center, humans at the edge, and decisions flow from customer inputs → AI → humans steering it.
00:00 Existential Dread & Hope.
02:56 AI Replaces Hierarchy.
Next-generation optoelectronic systems (devices that convert light to electrical energy) leverage organic semiconductor-based indoor energy-autonomous architectures for cutting-edge applications. Notably, organic semiconductors possess mechanical flexibility, solution processability, and bandgap-tunable optoelectronic properties, making them highly lucrative for indoor power generation via organic photovoltaics (OPVs), as well as for spectrally selective photodetection through organic photodetectors (OPDs). Unfortunately, technological progress made in the fields of OPVs and OPDs has largely been separate, necessitating further research for the development of bifunctional OPV-OPD systems for concurrent energy harvesting and photodetection.
Additionally, the potential self-powered operation of such systems is restricted by conflicting charge transport kinetics, especially in the electron and hole transport layers (ETLs and HTLs, respectively). This limitation impacts device durability and stability and increases fabrication costs, making it indispensable to find new HTL materials such as poly(3,4-ethylenedioxythiophene), 2-(9H-carbazol-9-yl)ethyl]phosphonic acid self-assembled monolayer, MoOx, NiOx, and V2O5, beyond conventional options.