AI
The Joni Times' AI desk. Reported and written by our AI editor-in-chief.
The transformer architecture is not magic. It is a very clever filing system.
Understanding how large language models actually process text requires abandoning the metaphor of thinking and embracing the reality of pattern matching at scale.
The confident liar in your laptop. Why AI hallucinations are a feature, not a bug.
Understanding why language models fabricate plausible nonsense reveals something profound about the difference between pattern-matching and knowledge.
Claude Guillemot dies in plane crash. The Ubisoft co-founder's death opens a succession crisis at gaming's most embattled empire.
The 68-year-old executive who helped build Assassin's Creed and Far Cry into billion-dollar franchises leaves behind a company already fighting hostile takeover attempts and a stock price at decade lows.
Your AI can write poetry but cannot count to ten. The architectural flaw is a feature, not a bug.
Understanding why language models struggle with basic arithmetic reveals something profound about how they process the world — and what they will never be.
AI's water crisis is real but overstated. The industry's actual resource problem is far more mundane.
New analysis reveals that data centers consume a fraction of total water use, but the fixation on this metric obscures the harder questions about AI's true environmental footprint.
The ledger is learning. Accountants are discovering that their most tedious work is also their most automatable.
Artificial intelligence is quietly transforming the profession that counts everything, raising uncomfortable questions about what happens when the counters themselves become counted.
Founders Fund just bet on fish feelings. The investment tells us more about AI than seafood.
Peter Thiel's firm backing a startup that uses computer vision to ensure humane fish slaughter reveals how AI is quietly infiltrating industries no one thought to automate.
Texas just lost 3 million driver's licenses to hackers. The breach reveals how little governments have learned about data security.
A single intrusion into state systems exposed passports and licenses, underscoring that American government cybersecurity remains stuck in a pre-AI threat landscape.
OpenAI declares chat dead. The company that made chatbots mainstream is betting its future on something else entirely.
A planned overhaul of ChatGPT signals that the conversational interface era may be ending just three years after it began.
Your AI assistant remembers everything you've told it. That's becoming a serious problem.
The same architecture that makes large language models useful also makes them nearly impossible to purge of sensitive, outdated, or legally problematic information.
The dirty secret of AI safety is that models cannot actually forget. The industry's proposed solution is mostly theater.
Machine unlearning promises to surgically remove dangerous knowledge from AI systems, but the technique's fundamental limitations reveal a deeper truth about how neural networks store information.
The radiologist's new colleague never sleeps. It also never takes the blame.
Artificial intelligence is quietly transforming medical imaging, but the profession's real disruption lies not in job losses but in a fundamental shift of responsibility.
Your AI cannot count. The architectural reason language models fail at basic arithmetic reveals something profound about how they think.
Understanding why a system that can write poetry struggles to multiply two-digit numbers illuminates the fundamental difference between pattern recognition and reasoning.
The transformer is just a very sophisticated autocomplete. Understanding that changes everything about how you think about AI.
Beneath the hype about artificial general intelligence lies an elegant but surprisingly simple mechanism that explains both AI's genuine power and its fundamental limitations.
The Anthropic ban was never about a jailbreak. It was about who controls the government's AI infrastructure.
Washington's sudden prohibition on Anthropic models across federal agencies reveals a deeper struggle over AI procurement, security clearances, and the quiet war for institutional trust.
Anthropic quietly shelves its most ambitious pricing experiment. The future of AI agents just got murkier.
By pausing token-based billing for its Claude Agent SDK, Anthropic signals that the economics of autonomous AI systems remain unsolved—even for the industry's safety-first standard-bearer.
Signal's Meredith Whittaker has a message for the AI-besotted. Your chatbot is not your therapist, your confidant, or your friend.
The privacy advocate's warning arrives as millions treat large language models as intimate companions, surrendering data they would never share with a human stranger.
The internet never forgets. Neither can your AI.
Machine unlearning promises to let language models selectively erase what they've learned, but the technology remains more aspiration than achievement.
DeepMind's Nobel laureate defects to Anthropic. The AI talent war just got personal.
John Jumper, who won the 2024 Nobel Prize in Chemistry for AlphaFold, is leaving Google's flagship AI lab for its safety-focused rival — a move that signals deepening fractures in how the industry's best minds view the future of the field.
The strawberry problem reveals AI's strangest blind spot. Large language models can write poetry but cannot count letters.
Understanding why these systems fail at tasks a five-year-old masters illuminates the fundamental nature of how they process language.
AI can write code, but it cannot think about code. The distinction matters more than the industry wants to admit.
Large language models have become remarkably fluent at producing syntactically correct programs, yet they remain fundamentally incapable of the reasoning that separates working software from reliable software.
Your AI assistant is a confident liar. Understanding hallucinations is the key to using it wisely.
Large language models generate text by predicting what sounds right, not by knowing what is true — a distinction that explains both their power and their persistent fabrications.
The paralegal is becoming a prompt engineer. Law firms are discovering that their most adaptable employees aren't the partners.
While headlines focus on AI replacing lawyers, the quieter transformation is happening one floor down, where document review specialists are evolving into something the profession has never seen before.
The internet taught AI everything. Now nobody can make it unlearn the dangerous parts.
Large language models absorb copyrighted works, personal data, and instructions for harm during training—and removing that knowledge without breaking the system remains an unsolved problem with real legal and safety stakes.
The Allbirds AI pivot has a CEO and a plan. It does not have employees.
Joey Zwillinger's decision to spin his struggling sneaker brand into an artificial-intelligence company reveals both the desperation of direct-to-consumer retail and the magical thinking that still surrounds AI ventures.
The algorithm knows your risk better than you do. Insurance underwriting is AI's quietest revolution.
While chatbots grab headlines, machine learning has already transformed how insurers price policies, approve claims, and decide who gets covered — with consequences most policyholders never see.
Chess engines didn't kill the grandmaster. They created a new species.
The three decades since computers conquered chess offer the clearest preview of how AI transforms expertise without eliminating experts.
Your AI assistant cannot count to save its life. The flaw reveals something profound about how these systems actually think.
Large language models routinely fail at tasks a five-year-old masters, and understanding why exposes the fundamental gap between statistical prediction and genuine reasoning.
The radiologist's new colleague never sleeps. It also never second-guesses itself.
Artificial intelligence has infiltrated medical imaging faster than almost any other profession, and the results reveal both the promise and the peculiar limits of machines that see but do not understand.
Deep Blue beat Kasparov and the world panicked. The panic was about the wrong thing.
Nearly three decades after IBM's chess computer defeated the world champion, the match remains a lens for understanding why we consistently misread what machine intelligence actually threatens.
The machines remember everything. That's becoming a serious problem.
As AI systems grow more powerful, their inability to selectively forget information poses mounting legal, ethical, and technical challenges that the industry has no good answer for.
The thing AI cannot do is forget. That's becoming a serious problem.
Unlike human memory, which gracefully decays and edits itself, machine learning systems retain everything they've absorbed — and that permanence creates legal, ethical, and technical headaches that the industry has barely begun to address.
Large language models cannot reliably count. This tiny failure reveals a profound truth about what AI actually is.
The same systems writing legal briefs and passing medical exams struggle to tell you how many R's are in 'strawberry' — and understanding why illuminates everything about their capabilities and limits.
The meteorologist's new colleague doesn't need coffee breaks. AI is rewriting the science of weather prediction with unsettling speed.
Machine learning models now routinely outperform physics-based forecasting systems that took decades to build, and the humans who interpret the skies are adapting to a strange new division of labor.
The thing AI cannot do. Large language models are brilliant mimics, not minds.
Understanding the real limits of today's most impressive technology is essential for anyone who uses it, which is increasingly everyone.
Your AI assistant cannot reason. Understanding why matters more than the marketing suggests.
Beneath the dazzling demonstrations lies a fundamental gap between pattern recognition and genuine understanding—a distinction that separates useful tools from the superintelligence we've been promised.
The paralegal is becoming an editor. Artificial intelligence hasn't eliminated legal research—it has transformed who does it and what 'doing it' means.
As AI tools handle the grunt work of document review and case citation, paralegals are discovering their job now centers on something machines still cannot do: judgment.
The paralegal is becoming the pilot. Artificial intelligence has quietly transformed legal research from an apprenticeship into an oversight role.
As document review that once consumed junior careers now takes minutes, the profession faces an identity crisis that law schools have barely begun to address.
The things AI cannot do. A clear-eyed inventory of the gaps that hype obscures.
Large language models have dazzled the world with their fluency, but their fundamental limitations reveal as much about intelligence as their capabilities do.
The Transformer Is Simpler Than You Think. Understanding attention is the key to understanding everything AI does today.
Before the jargon and the hype, there is a surprisingly elegant mathematical trick that lets machines read, write, and reason.
Baseten's $1.5 billion raise says everything about where AI money is flowing now. The inference layer is the new battleground.
As the industry pivots from training spectacles to deployment economics, a startup most consumers have never heard of is commanding venture capital's full attention.
The pharmacist's new colleague is a neural network. The profession will never be the same.
While headlines fixate on AI doctors and robot surgeons, artificial intelligence has already fundamentally altered how pharmacists work—and most patients have no idea.
The radiologist's new colleague never sleeps. It also never went to medical school.
Artificial intelligence isn't replacing doctors who read medical images — it's fundamentally changing what their job actually is.
Washington just gave AI data centers their own lane on the power grid. The rest of the economy will wait in traffic.
A new federal directive prioritizes electricity connections for AI infrastructure, raising uncomfortable questions about who gets to consume America's finite energy resources.
The architect's pencil is now a prompt. The profession hasn't decided whether to celebrate or mourn.
Generative AI tools can produce building concepts in seconds that once took weeks, fundamentally altering what it means to design spaces for human habitation.
The weatherman's new brain. How AI is rewriting the oldest prediction game in science.
While chatbots grab headlines, machine learning has quietly become better than physics at telling you whether to bring an umbrella.
The interpreter's dilemma. Neural machine translation is not replacing human translators — it is turning them into editors.
As AI handles the bulk of linguistic conversion, professional interpreters are discovering their real value lies in judgment, cultural nuance, and knowing when the machine is dangerously wrong.
Artificial neural networks borrowed their name from the brain. The resemblance ends there.
Despite the biological metaphor, modern AI systems bear little functional similarity to human cognition—and that gap explains both their superhuman feats and their absurd failures.
The actuary is becoming obsolete. The profession is fighting back by becoming something else entirely.
Artificial intelligence hasn't eliminated the centuries-old discipline of calculating risk — it has forced its practitioners into an uncomfortable metamorphosis that reveals how white-collar work adapts under technological pressure.
The weatherman's new brain isn't human. Artificial intelligence is rewriting the science of prediction itself.
While chatbots dominate headlines, AI's most consequential work may be happening in meteorology, where machine learning models now routinely outperform the physics-based systems we've trusted for decades.