The internet has a brain, and its name is Wolfram Alpha / The New Daily
reprinted from the New Daily – Jackson Stiles
Rather than simply finding and regurgitating information, this search engine marries, melds, culls, gleans and kneads it, giving you the best possible answer to what you ask.
That, at least, is what makes it unique. Last month, it tried to become just like everyone else by debuting image recognition – an inferior copy of what Google already does quite well.
For now, Wolfram’s ability to read images is, by its own admission, limited, but it is learning. It is this ability to learn, like a brain, that makes the engine useful.
In a speech in 2010, its creator – computer scientist Dr Stephen Wolfram – said he dreamed ever since he was a kid (he published his first scientific paper at the age of 15) of making as much human knowledge as possible “computable”.
“I’d always assumed that to make progress, I’d essentially have to replicate a whole brain,” he said.
Stephen Wolfram wanted to create a search engine with a brain.
Instead, Dr Wolfram gave us this beautiful, geeky guardian of facts. The Stephen Fry of search engines, if you will. The quiz master of the web.
For example, ask it ‘who is Kim Kardashian?’ and you are not greeted by X-rated images of the celebrity in various states of rumptastic undress, but instead a list of factoids, such as her height (1.57 metres), weight (54 kilograms) and middle name (Noel).
“It doesn’t come back with three million searches,” tech futurist Morris Miselowski told The New Daily.
“It comes back with 10 or so facts that are really tuned in to what it is you are looking for.”
To become truly intelligent is the goal.
“What it’s really pushing towards is artificial intelligence. That was always where it was headed – to know more about what we were looking for than we did,” Mr Miselowski said.
This, it seems, is the future.
“Google and the other search engines are very much heading in that direction,” he said.
“We’ll come to a time very quickly where search engines as we know them will be old and antiquated and we’ll wonder how we ever bothered with a million different answers to something.”
Wolfram Alpha works by using “very sophisticated algorithms” to pull together information from reliable sources, said University of Technology Sydney senior lecturer Maureen Henninger, an information retrieval expert.
“It’s a terrific search engine for facts and computation,” Ms Henninger said.
“I use it all the time for when I want a fact, an actual fact.
“Whereas if you use Google, it’s going to do a whole lot of personalised searching and contextualising according to your comfort zone, and so on.”
Here are some of the cool things it can do.
Type in ‘create password’ and fiddle with the options that appear to save yourself the headache of inventing one.
Probabilities
Type in ‘poker hand probabilities’ to find out your chances of winning your bet.
Track satellites in real time
Type in ‘International Space Station’ to find out over what part of the Earth the research facility is currently hovering.
Find words
Can you remember part of a word, but not the whole thing? Just type in the bits you remember and fill in the bits you don’t with a line.
Track space stations and satellites from your study.
For example, ‘_cious’ returns just one result: ‘vicious’.
Plan your exercise regime
Type in something like ’30 min walk calories’ and Wolfram will tell you how many calories you can expect to burn, depending on factors like your speed, gender and weight.
Find yourself
Not quite in the metaphysical sense. But type in ‘where am i?’ and Wolfram will use your IP address to calculate just that.
Website battles
Want to quickly compare the ranking and traffic of two websites? Type both addresses into the search bar with “vs” in between and you’ll have the answer.
Compare the Empire State Building (front) to the new World Trade Centre behind it.
Enter your weight, gender, drinks consumed (if you can remember), time you consumed them in and you’ll get your reading.
Detailed nutritional information for a massive variety of foods, meals and products.
Know what to expect at the doctor
The search engine will use data to predict what kind or brand of medication you’ll be prescribed for certain conditions.
What is $10 dollars in 1920 worth today?
Go to any point in time with any amount of money and find out how the dollar has changed through history.
Compare man-made structures
This includes their size, features and little-known details.
Frequently Asked Questions
Q: What did Wolfram Alpha reveal about the potential and limits of computational knowledge engines?
Wolfram Alpha represented a genuinely different approach to machine knowledge than search engines: rather than indexing human-created content and returning links, it computed answers from curated, structured knowledge using Mathematica’s computational capabilities. This approach proved genuinely powerful for certain categories of question (mathematical computation, scientific data, precisely defined factual queries) and genuinely limited for others (natural language questions, contextual reasoning, the messy ambiguity of most human queries). Its most important contribution to the trajectory of machine intelligence was demonstrating that structured, computable knowledge could answer questions directly rather than returning documents — a model that prefigured the answer-first design of modern AI assistants, even though the underlying technology was completely different.
Q: How does Wolfram Alpha fit in the longer trajectory toward large language model AI?
Wolfram Alpha sits in an interesting position in the trajectory toward modern AI: it approached the ‘machines that answer questions’ problem through curated structured knowledge and computation — essentially a human-built knowledge graph with computational capabilities; large language models approached the same problem through statistical learning from massive text corpora — essentially pattern recognition over human-generated text at scale; and the current frontier is attempting to combine both — LLMs with access to structured knowledge, computation tools, and verified data sources (which is how modern AI systems including Claude use tools like code execution and search). Wolfram Alpha’s limitations pointed directly toward what language models would need to be good at (natural language understanding, contextual reasoning, handling ambiguity) and what language models would need tools for (precise computation, current data, authoritative structured knowledge).
Q: What does the history of machine knowledge tools reveal about how technology problems get solved over time?
The history from Wolfram Alpha to modern AI reveals the typical pattern of technology problem-solving: an approach that works well for a subset of problems (structured computation for precise queries) inspires confidence and investment but hits fundamental limits; an apparently unrelated approach (statistical learning from text) solves different parts of the problem and inspires its own enthusiasm; and the synthesis of multiple approaches produces something more capable than either predecessor. The lesson for anyone trying to read technology trajectories is: the limits of the current best solution point toward the direction of the next breakthrough; and the most significant advances often come from people who understood why the previous approach failed rather than people who tried to make it better on its own terms.
Q: How can I book Morris Misel for a AI history, technology futures, or digital intelligence keynote?
Contact the team at morrismisel.com/event-organisers.
reprinted from the New Daily – Jackson Stiles Rather than simply finding and regurgitating information, this search engine marries, melds, culls, gleans and kneads it, giving you the best possible answer to what you ask. That, at least, is what makes it unique. Last month, it tri.
When signals like The internet has a brain, and its name is Wolfram emerge, organisations that engage early have the advantage of choosing their response rather than reacting to events. That gap between those who prepared and those who did not is where competitive positioning is actually made or lost.
The most important question is not whether The internet has a brain, and its name is Wolfram will matter, but how quickly it will matter in your specific context. Leaders benefit most from mapping the ripple effects early — not just the direct impact but the second and third-order consequences that arrive later and hit harder. That is the practical work of foresight.
