Skip to main content

Inception Emerges From Stealth With a New Type of AI Model

2 months 2 weeks ago
Inception, a Palo Alto-based AI company founded by Stanford professor Stefano Ermon, claims to have developed a novel diffusion-based large language model (DLM) that significantly outperforms traditional LLMs in speed and efficiency. "Inception's model offers the capabilities of traditional LLMs, including code generation and question-answering, but with significantly faster performance and reduced computing costs, according to the company," reports TechCrunch. From the report: Ermon hypothesized generating and modifying large blocks of text in parallel was possible with diffusion models. After years of trying, Ermon and a student of his achieved a major breakthrough, which they detailed in a research paper published last year. Recognizing the advancement's potential, Ermon founded Inception last summer, tapping two former students, UCLA professor Aditya Grover and Cornell professor Volodymyr Kuleshov, to co-lead the company. [...] "What we found is that our models can leverage the GPUs much more efficiently," Ermon said, referring to the computer chips commonly used to run models in production. "I think this is a big deal. This is going to change the way people build language models." Inception offers an API as well as on-premises and edge device deployment options, support for model fine-tuning, and a suite of out-of-the-box DLMs for various use cases. The company claims its DLMs can run up to 10x faster than traditional LLMs while costing 10x less. "Our 'small' coding model is as good as [OpenAI's] GPT-4o mini while more than 10 times as fast," a company spokesperson told TechCrunch. "Our 'mini' model outperforms small open-source models like [Meta's] Llama 3.1 8B and achieves more than 1,000 tokens per second."

Read more of this story at Slashdot.

BeauHD

Signal will withdraw from Sweden if encryption-busting laws take effect

2 months 2 weeks ago
Experts warned the UK’s recent 'victory' over Apple would kickstart something of a domino effect

Signal CEO Meredith Whittaker says her company will withdraw from countries that force messaging providers to allow law enforcement officials to access encrypted user data, as Sweden continues to mull such plans.…

Connor Jones

Amazon Uses Quantum 'Cat States' With Error Correction

2 months 2 weeks ago
An anonymous reader quotes a report from Ars Technica: Following up on Microsoft's announcement of a qubit based on completely new physics, Amazon is publishing a paper describing a very different take on quantum computing hardware. The system mixes two different types of qubit hardware to improve the stability of the quantum information they hold. The idea is that one type of qubit is resistant to errors, while the second can be used for implementing an error-correction code that catches the problems that do happen. While there have been more effective demonstrations of error correction in the past, a number of companies are betting that Amazon's general approach is the best route to getting logical qubits that are capable of complex algorithms. So, in that sense, it's an important proof of principle. Amazon's quantum computing approach combines cat qubits for data storage and transmons for error correction. Cat qubits are quantum bits that distribute their superposition state across multiple photons in a resonator, making them highly resistant to bit flip errors. Transmons are superconducting qubits that help detect and correct phase flip errors by enabling weak measurements without destroying the quantum state. Meanwhile, a phase flip is a quantum error that alters the relative phase of a qubit's superposition state without changing its probability distribution. Unlike a bit flip, which swaps a qubit's state probabilities, a phase flip changes how the quantum states interfere, potentially disrupting quantum computations. By alternating cat qubits with transmons, Amazon reduces the number of hardware qubits needed for error correction. Their tests show that increasing qubits lowers the error rate, proving the system's effectiveness. However, rare bit flips still cause entire logical qubits to fail, and transmons remain prone to both bit and phase flips. If you're still entangled in this story without decohering into pure quantum chaos, kudos to you!

Read more of this story at Slashdot.

BeauHD

Satya Nadella Argues AI's True Value Will Come When It Finds Killer App Akin To Email or Excel

2 months 2 weeks ago
Microsoft CEO Satya Nadella argues that AI's success should be measured by its impact on economic growth rather than achieving artificial general intelligence (AGI), emphasizing that true progress will come when AI finds a transformative application akin to email or Excel. The Register reports: "Us self-claiming some AGI milestone, that's just nonsensical benchmark hacking," the chief executive said during an appearance on podcaster Dwarkesh Patel's YouTube show this month. Nadella thinks a better benchmark for AI's success should be its ability to boost a country's gross domestic product. "When we say: 'Oh, this is like the industrial revolution,' let's have that industrial revolution type of growth. That means to me, 10 percent, seven percent for the developed world. Inflation adjusted, growing at five percent, that's the real marker." Nadella suggested that growth hasn't eventuated because it's going to take time before folks understand how to use AI effectively, assuming they find a use for it -- just as it took some years for the personal computer to find its feet. "Just imagine how a multinational corporation like us did forecasts pre-PC, and email, and spreadsheets. Faxes went around, somebody then got those faxes and then did an inter-office memo that then went around, and people entered numbers, and then ultimately a forecast came out maybe just in time for the next quarter," Nadella explained. "Then somebody said: 'Hey, I'm just going to take an Excel spreadsheet, put it in an email, send it around, people will go edit it, and I'll have a forecast.' The entire forecasting business process changed because the work artifact and the workflow changed. That is what needs to happen with AI being introduced into knowledge work," the CEO said. [...] "Don't conflate knowledge worker with knowledge work," he said. "The knowledge work of today could probably be automated, [but] who said my life's goal is to triage my email?" Instead, he argues AI agents will allow workers to focus on higher-value tasks. Whether this is actually how it'll play out, or whether enterprises will take this as an opportunity to reduce costs by cutting staff remains to be seen. ... "Today, you cannot deploy these intelligences unless and until there's someone indemnifying it as a human," he said.

Read more of this story at Slashdot.

BeauHD