Tag Archives: Artificial Intelligence

Chinese AI company DeepSeek released a set of software tools on September 30. They are designed specifically for Huawei’s Ascend AI chips, a move that strikes directly at one of Nvidia’s most durable advantages: the software ecosystem built around its hardware. The new DeepSeek Huawei chip tools include six open-source modules, according to reporting from the South China Morning Post. They are built to make Huawei’s chips easier for developers to actually use.

The centerpiece is an Ascend-compatible version of TileLang. DeepSeek originally built this programming language for high-performance computation on Nvidia hardware. It has now been adapted to run on Huawei’s chips instead.

Why the DeepSeek Huawei chip tools target software, not just chips

Nvidia’s dominance in AI computing rests as much on its CUDA software platform as on its silicon. Developers who have spent years building tools and workflows around CUDA face real friction switching to alternative hardware, even when that hardware is competitively priced or more available. DeepSeek is attempting to lower that switching cost directly by porting TileLang to Huawei’s Ascend platform. GitHub documentation describes the result as offering “native code generation, automatic scheduling, and synchronisation” for Ascend chips.

The South China Morning Post reported the release is part of a broader Chinese effort. The goal is an “independent and controllable” AI software ecosystem, reducing the country’s dependence on American technology. That effort comes at a time when U.S. export controls have restricted the sale of advanced Nvidia chips to Chinese buyers.

The hardware gap DeepSeek is trying to close

DeepSeek’s chief executive, Liang Wenfeng, addressed the underlying hardware gap directly in comments reported by Digital Citizen in July. He said Huawei’s Atlas 950 SuperPoD system could functionally replace Nvidia’s GB200 and GB300 platforms for many workloads. That is true even though it currently takes roughly four Huawei accelerators to match the performance of a single Nvidia GPU. Wenfeng argued that availability matters more than raw performance when superior Nvidia chips cannot be bought in sufficient quantities due to export restrictions. He suggested Chinese firms would accept paying a 50% to 200% premium for Huawei hardware they can actually obtain.

He also estimated, in those July remarks, that Chinese AI labs remain roughly two years behind their American counterparts on model capability. The new software tools do not close that gap on their own. They are meant to help narrow it over time by making Chinese hardware more usable.

What Ascend 950 support means in practice

With direct software support now available, Huawei’s Ascend 950 accelerators become a more practical option for Chinese developers building and training AI models. That is according to the South China Morning Post’s reporting. It matters for DeepSeek’s own operations too. The company has said it currently works with computing capacity equivalent to roughly 20,000 Nvidia H100 GPUs, a fraction of the scale used by the largest U.S. labs.

What comes next for Huawei’s chip ecosystem

The open-source release does not resolve the performance gap between Huawei’s chips and Nvidia’s newest hardware. But it removes one of the practical barriers to adoption inside China. Whether other Chinese AI companies build on top of DeepSeek’s tools, rather than maintaining their own workarounds, will determine how much traction the effort gains. Continued U.S. export restrictions on advanced Nvidia chips give Chinese developers a strong incentive to make that switch work.

Why this matters outside China

For chipmakers and cloud providers outside China, a more usable Huawei ecosystem sends a signal. The current export-control strategy is accelerating the very domestic alternative U.S. policy aimed to prevent. It also gives global AI developers a second software stack to watch, one built outside the Nvidia-dominated toolchain that has underpinned most AI development to date.

What people want to know about the DeepSeek-Huawei tools

Related AI policy coverage

• Nvidia’s chip export loophole into China
• Google, Anthropic and OpenAI on cyber AI models
• AMD’s climb toward a trillion-dollar market cap

Source notes

• South China Morning Post — China’s DeepSeek open-sources tools to help Huawei chips supplant Nvidia in AI. scmp.com
• Digital Citizen — DeepSeek CEO says Huawei’s AI hardware can replace Nvidia racks despite lower per-GPU performance. digitalcitizen.life

OpenAI used its 2026 DevDay conference on September 29 to introduce a product built around a simple pitch: an AI system that keeps working after you stop looking at it. The new OpenAI Dots AI agents run continuously in the background. They carry out tasks across ChatGPT, text messaging, email and Slack, with no need for a human to keep the conversation open.

The announcement, reported by Business Standard and other outlets covering DevDay, arrived alongside a second release. That release is GPT-6.1 Sol, a cheaper model aimed at coding and everyday professional tasks.

What the OpenAI Dots AI agents actually do

Dots is built on GPT-6 Astra. It comes with its own dedicated cloud computing resources and browser access, letting it interact with connected tools and services on a user’s behalf. According to Business Standard’s coverage of the launch, Dots can handle recurring work and delegated tasks. Users can set permissions that require confirmation before it takes certain actions. For now, access is limited to subscribers on OpenAI’s Pro, Business Premium and Enterprise tiers.

The always-on framing sets Dots apart from a standard chatbot session, which ends the moment a user closes the app. OpenAI’s pitch is that Dots can pick up multi-step projects and check back in on progress. It can keep working through tasks that would otherwise require a person to return and re-prompt the system repeatedly.

GPT-6.1 Sol: performance close to Astra at a fraction of the cost

GPT-6.1 Sol is positioned as the budget option in the GPT-6 family. It is built to approach the coding performance of the flagship GPT-6 Astra model while costing far less to run. Coverage from AI Weekly cited a price of roughly $2 per million input tokens, a fraction of what flagship-tier models typically cost. The model supports a 1.05 million-token context window. It can generate up to 128,000 output tokens in a single response, according to Business Standard’s report.

OpenAI also said safety testing showed improvements in five of eight production safety categories, compared with an earlier version of Sol. The company noted that cybersecurity vulnerability generation in Sol still lags behind GPT-6 Astra.

A new top-tier subscription plan

Alongside the model releases, OpenAI introduced ChatGPT Pro 500. It is a $500-per-month plan offering the highest usage allowances among its Pro tiers, plus access to a new “Ultrafast” service tier for GPT-6 Astra. OpenAI also unveiled several other tools at DevDay. These include ChatGPT Spaces, a team collaboration workspace; Living Pages, documents that update alongside a project’s progress; Codex Cloud, a browser-based coding environment; and new Agents and Decisions APIs for developers.

What Dots and Sol change starting now

For businesses already using ChatGPT’s higher-tier plans, Dots marks a shift. It moves users from prompting an assistant toward delegating standing tasks to it, provided they are comfortable with OpenAI’s permission model. For developers, GPT-6.1 Sol’s pricing makes near-frontier coding performance available at a lower-tier cost. That could pressure rival AI labs offering similarly priced mid-tier options.

Where this fits in the wider AI race

The launch lands in a week already dense with AI news, from Anthropic’s leaked IPO filing to a White House-brokered safety accord signed by OpenAI and five other AI companies. Positioning Dots as an always-on agent puts OpenAI in more direct competition with other companies building autonomous “agentic” tools. That category has become one of the most closely watched fronts in AI development over the past year. Google, Anthropic and several well-funded startups have all shipped their own agentic tools in recent months. OpenAI chose to build Dots directly into its existing ChatGPT subscription tiers, rather than launching it as a separate product. That suggests the company wants agentic features to feel like a natural upgrade, not a new purchase decision, for its largest customers.

Questions readers are asking about OpenAI’s Dots agents

Further reading on Tamara News

• What happened to OpenAI’s GPT-6.1 Astra
• AI labs face a new antitrust lawsuit
• OpenAI’s rogue agents and government websites

References

• Business Standard — OpenAI DevDay 2026: Dots agent, GPT-6.1 Sol, new plans and more announced. business-standard.com
• AI Weekly — OpenAI News Today. aiweekly.co

Ohio state lawmaker Tristan Rader is pushing to claw back sales-tax exemptions worth more than $1.5 billion. Those data center tax breaks let Amazon, Google and Meta avoid tax last year alone, a figure he says blew past original state estimates by more than tenfold. Rader, a Democrat representing Lakewood, wants new data-center-specific taxes. He also wants requirements that the companies pay more toward the power and electrical infrastructure their facilities consume.

How the data center tax breaks ballooned

Ohio’s sales-tax exemption for data centers was designed to attract investment. It lets operators avoid tax on qualifying equipment purchases in exchange for long-term commitments to build and hire in the state. Rader says the exemption’s actual cost to Ohio surged past $1.5 billion last year. That is more than ten times what state officials originally projected when the incentive was designed. The overshoot is large enough that it has drawn bipartisan attention to how the program is structured going forward.

Why one lawmaker is pushing back now

Rader’s objection is blunt: he argues Amazon, Google and Meta no longer need the incentive to justify building in Ohio. “They seem to have more money than God and they’re able to build without the need for these types of incentives,” he said. That framing casts the exemptions as an unnecessary subsidy to some of the world’s most profitable companies. It is not, he argues, a targeted tool for attracting investment that would not otherwise happen. His proposals include new data-center-specific taxes. He also wants operators to contribute more directly to the cost of power and electrical grid upgrades.

Ohio isn’t acting alone

The pushback fits a broader pattern of states rethinking how generously they court data centers. Ohio Governor Mike DeWine paused new applications for the sales-tax exemption in May 2026, effectively freezing the program while the state reassesses its cost. New York went further in July 2026, enacting a one-year statewide moratorium on new hyperscale data centers altogether. Both moves reflect growing concern among state officials. Hosting these facilities mainly brings construction jobs and a smaller number of permanent operations roles. Officials increasingly doubt that benefit still outweighs the tax revenue given up, and the strain the facilities place on local power grids.

What the companies have said

Amazon, Google’s parent Alphabet, and Meta did not immediately respond to requests for comment on Rader’s proposal. Their silence leaves the political framing largely to critics for now. All three companies have previously defended data-center investment in other states. They point to local job creation, community infrastructure spending, and long-term tax revenue once exemption periods expire.

What happens next for data center incentives nationally

Rader’s proposal would need to move through the Ohio legislature. Its prospects depend on how much appetite Republican leadership has for revisiting an incentive program tied to some of the state’s largest recent capital investments. More broadly, expect other state legislatures to watch Ohio and New York closely. Either state might successfully claw back incentives, or hold firm on a moratorium without scaring off future investment. If so, other states weighing similar hyperscale data-center proposals are likely to write tighter terms into their own incentive packages. Utility regulators are also part of this conversation. Much of the recent criticism centers as much on the strain hyperscale facilities place on regional power grids as on the tax revenue foregone. Several states are separately weighing whether data-center operators should pay a larger share of the transmission and generation capacity their facilities require.

Frequently asked questions

How large are the data center tax breaks in question?

Ohio’s sales-tax exemption for data centers cost the state more than $1.5 billion last year, according to state Rep. Tristan Rader, more than ten times the original estimate.

Which companies are named in the dispute?

Amazon, Google and Meta are the companies Rader specifically cited as beneficiaries of Ohio’s data center sales-tax exemption.

What is Rader proposing instead?

New data-center-specific taxes and requirements that operators pay more toward the cost of power and electrical infrastructure their facilities require.

Have other states taken similar action?

Yes. Ohio’s governor paused new exemption applications in May 2026, and New York enacted a one-year moratorium on new hyperscale data centers in July 2026.

Have Amazon, Google or Meta responded?

None of the three companies immediately responded to requests for comment on the proposal.

Why states offered these incentives in the first place

Sales-tax exemptions for data centers became a common economic-development tool over the past decade. States competed for the large capital investments hyperscale computing facilities represent, often running into the billions of dollars per site. The pitch to state legislatures was straightforward: exempt the equipment purchases from tax. In exchange, the state gains construction jobs, a smaller number of permanent operations positions, and property-tax revenue once any abatement period ends. What has changed is the sheer scale of recent AI-driven data center buildouts. That scale has made the true cost of these exemptions far larger than the modest programs originally designed for a handful of facilities per state.

More on the AI infrastructure buildout

For more on the infrastructure race behind this fight, see our reporting on Oracle’s delayed Project Jupiter data center and AMD’s climb to a trillion-dollar valuation.

Sources

• Benzinga — Amazon, Google and Meta Face Pushback Over Data Center Tax Breaks. https://www.benzinga.com/markets/tech/26/09/61677645/amazon-google-and-meta-face-pushback-over-data-center-tax-breaks-lawmaker-says-they-have-more-money-than-god
• PYMNTS — Amazon, Microsoft and Google Under Fire for Data Center Resource Use. https://www.pymnts.com/cpi-posts/amazon-microsoft-and-google-under-fire-for-data-center-resource-use/