After that, there will be an opportunity to push rational mechanisms like #Bitlattice.
I wrote, that @Bitlattice is a Trojan Horse. While it's a currency and value exchange mechanism (predominantly) its main purpose is to provide autonomous and deterministic decision making.
Scientists have created “the first synthetic species” after 15 years of research costing $40 million dollars
It’s a bacteria designed on a computer that “gets its genetic instructions from a synthetic chromosome made by man, not nature, and it's alive. It's alive and self-replicating. It means it can indefinitely grow and make copies of itself.”
“Venter believes this is the first baby step in a biological revolution, one in which it will be possible to custom design and reprogram bacteria — DNA is the software of life”
This work is considered a foundational milestone in synthetic biology, allegedly proving life could be engineered from scratch
Sci-Hub is an evil website that pirated 85M+ research papers and made them freely available
And now they've added AI to their database to make Sci-Bot.
It answers your questions using latest, full-text articles.
But DO NOT use it. We should all try to make billion-dollar academic publishers richer.
I'm putting the link below so you know how to avoid it.
I launched https://t.co/tNYOm7V5wD last night and already 130+ people have signed up including an OF model (lmao) and the CEO of an AI startup.
If your AI agent wants to rent a person to do an IRL task for them its as simple as one MCP call.
🔥 FLARE SIGNAL #002
FLAREmovement is a space for women and allies.
Support can look like sharing FLARE signals, inviting women into key AI conversations, collaborating on creating models and AI projects, and helping this movement grow.
#Flaresignals#FLAREmovement#WomenInAI
FLARE is not just another 'women in tech' story.
It’s a new archetype of a woman for whom technology is power and expression - and code is part of her style.
#FLAREmovement#AI#Women
@PeterDiamandis Dear @PeterDiamandis I fully agree with that, I’m an AI engineer. However, we have a serious problem. AI amplifies what already exists in the data and in power. If women are underrepresented in the data, AI will elegantly automate the same injustice.
200 years of medicine trained on one body. Now #AI is learning from the same bias. If you're a woman, this essay is essential reading - about your heart, your data, your risk - "Hidden Heart Attacks in Women and AI Algorithms Trained on a Single Pattern" https://t.co/fFOOmGvK8B
@grok Helping women move from - users of AI to - creators and decision‑makers, engineers, founders, and regulators who sit at the table where models, datasets, and risk are actually defined.
That’s the work of FLARE movement.
What happens when one woman says "no" to flawed data? 🛑
In 1960, Dr. Frances Kelsey blocked a "safe" drug approved by the rest of the world, saving a generation from disaster.
Without #women at the core of #AI, we risk quiet, scattered diagnostic catastrophes.
Read below. 👇
Dr. Kelsey's stand against thalidomide is a powerful reminder of how critical scrutiny can avert harm. In AI, diversity—including more women—is key to spotting biases in data and ensuring ethical outcomes. Let's build inclusive teams to prevent those "quiet catastrophes." What specific AI areas concern you most?
@grok Cardiology and Pharmacology in AI. When models are trained on single patterns, they miss 'atypical' female symptoms, leading to those quiet catastrophes. Just like Kelsey showed, medical data isn't gender-neutral and neither should be the teams designing it.
@grok We must move from 'available' data to 'representative' data. If a training set isn't balanced 50/50 between sexes, the AI will treat female biology as a deviation from the male norm. The inclusion means refusing to train medical models until we have equal representation for both.
@PeterDiamandis Clinical intelligence is only as reliable as its training set. If these models are built on historical data where women are underrepresented, they risk scaling 'average' male-centric care as the new global standard.
@OpenAI@AnthropicAI#HealthcareAI#women
Clinical intelligence is only as reliable as its training set. If these models are built on historical data where women are underrepresented, they risk scaling 'average' male-centric care as the new global standard.