Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Launchpad
Be early to the next big token project
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
OpenClaw introduces the "Dream" memory system, which shares multiple similarities with Claude Code's leaked source code
According to 1M AI News monitoring, open-source AI assistant platform OpenClaw released v2026.4.5, featuring about 40 new features and over a hundred fixes, delivered by more than 60 contributors. This is the first major version update since Anthropic banned OpenClaw subscription access.
The most eye-catching new feature is an experimental “dreaming” memory system that splits backend memory integration into three cooperating stages: light sleep filters short-term memories, deep sleep handles durable persistence writes, and the REM stage discovers relationships and distills lasting insights. Each stage has its own independent scheduling and can run automatically when no user is interacting, along with a Dream Diary interface and debugging tools. In the Claude Code source code that was accidentally leaked on March 31, there happens to be a mechanism named autoDream as well—also automatically integrating, deduplicating, and eliminating memory conflicts during idle time, using a similar layered architecture: the index is always loaded, topics are read on demand, and history is only searched without loading.
Another similarity is prompt cache optimization. In this version, OpenClaw improves cache hit rates by deterministically ordering MCP tool definitions, normalizing system prompt fingerprints, stripping inline tool lists, and other measures. The Claude Code leaked source code shows that its internal design uses stable/dynamic prompt boundaries to maximize cache reuse; the optimization directions are nearly identical. Claude Code engineer Boris Cherny himself is also one of the contributors to OpenClaw’s cache improvements in this release.
However, the development records of relevant OpenClaw PRs indicate that these features were built well before the leak—finishing such a scale of feature migration in under a week is not realistic from an engineering perspective. A more likely explanation is that the two projects arrived at similar approaches when solving the same problem, and the leak gave the outside world the first chance to directly compare the internal designs of both.
Other major updates include: