Description RecallVerse is an AI-powered contact memory app that captures business cards, QR codes, photos and short voice memos, transcribes and enriches them, then uses semantic search and an AI Copilot to surface people from fuzzy, contextual queries, rank relevant referrals, and draft outreach messages. Professionals who meet lots of people use it to rediscover contacts by describing fragments of a memory (e.g., "who I met at SXSW who works in product"), get grounded answers pulled from their own notes (not hallucinations), and save time with one-tap actions and auto-sync to phone contacts; all parsing and search rely on AI while data is encrypted and the app states it does not train models on user data. Visit RecallVerse

Guess What... I Can Bend ..lol Pain isnt all the way gone but its gone enough not to bother me to death. How are you all?

Here's how to set up outbound calls with Pika AI Self. - Go to Pika AI Self and create your AI agent. - Train it with your personality, voice, and knowledge base. - Go to 'Skills and Connections' > 'Phone Calls' > 'Enable' - Your Pika Self gets assigned a unique phone number, and can call any number on your behalf. - Ask your Pika Self to call someone, and it will dial out and carry on the conversation in your voice.

lol https://www.youtube.com/shorts/szqXppELItw {caption from the vdeo} This scammer from a fake company called "Global Metrix" offered to recovery my stolen crypto currency. The problem for him is that I knew it was a scam, so I was surprised he offered to appear on a Zoom call. Undoubtedly to show off his deepfake technology. Except, one particular sentence unravelled his scam. Longer video on this scam is coming soon.

Now this is news ... At MIT Hard Mode 2026, a six-person team built an AI system that can temporarily move your hand for you. Called Human Operator, it combines a vision-language model, voice input, and electrical muscle stimulation – a technology that sends small currents through the skin to contract specific muscles – to physically guide a user’s hand and wrist through unfamiliar movements. The team describes it as a “human augmentation tool” designed to help people learn or perform actions they couldn’t manage on their own. Rather than displaying instructions or providing feedback after the fact, the system intervenes in the moment, nudging the body directly toward the right motion. Peter He, Ashley Neall, Valdemar Danry, Daniel Kaijzer, Yutong Wu, and Sean Lewis built the project and took first place in the “Learn Track.” The Hard Mode hackathon runs for 48 hours at MIT Media Lab, focused on intelligent physical systems that can sense, adapt, and respond to people in real time. How the Human Operator works What the team built is essentially a careful assembly of technologies that already existed, just never quite in this combination. A camera captures what the user sees. Voice input runs through Anthropic’s Claude API, which figures out what motion is needed and maps it to a sequence of muscle commands. Those commands then travel through an Arduino-based hardware stack to EMS electrodes on the wrist and fingers. In the demo footage, a hand waves back at someone, fingers find the right keys for a melody, and a fist curls into an OK sign. Each one is guided by the system, reading the situation and deciding it was time to move. The engineering stack reflects a deliberate choice about where AI sits in the interaction. Most consumer AI systems stop at text, voice, or screen output. Human Operator goes a layer deeper, into motion itself.https://www.youtube.com/watch?v=fCLxENGs7CY&t=13s The system tries to move with the body rather than surface instructions, which is an approach the team frames around helping users “learn and do things you normally cannot do.” Where that leads in terms of physical learning, accessibility, or new kinds of interfaces, however, is an open question.